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Content PSYCHOMETRIC AND BIOGRAPHICAL FACTORS
RELATED TO ATTAINMENT OF MANAGERIAL RESPONSIBILITY
BY ENGINEERS AND SCIENTISTS
by
Stanley Robert Weingart
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL OF BUSINESS ADMINISTRATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF BUSINESS ADMINISTRATION
April 1975
UMI Number: DP23924
All rights reserved
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This dissertation, written by
STANLEY R. WEINGART
under the guidance of the Faculty Committee, and
approved by all its members, has been presented to
and accepted by the Faculty of the Graduate School
of Business Administration in partial fulfillment
of the requirements for the degree of
DOCTOR OF BUSINESS ADMINISTRATION
Date___________April 28 . 1975
cJ?3c33 /~
Approved:
ju&SL
ACKNOWLEDGMENTS
The author is greatly indebted to a number of
individuals whose assistance and encouragement made the
completion of this study possible. Primary among this
group are the members of the author's committee. Their
patience, understanding, and kindness were deeply appre
ciated.
Of special significance was the invaluable guid
ance and assistance of Dr. Glen Grimsley, the committee
chairman. He was a hard task master for which I am
thankful, but more than that, he has been a true friend
and colleague. For that I am truly grateful.
To the faculty of the Management Department and
especially to Dr. John E. Flemming, its chairman, who en
couraged and even better yet, employed the author, par
ticular thanks is due.
Finally, thanks to David, Sheryl, and Richard
Weingart who have patiently waited so long for Dad to
spend more time with them. It is hoped that this effort
will encourage them to seek knowledge and truth in their
future endeavors whatever they may be.
TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS ........................................ ii
LIST OF TABLES .................................. v
Chapter
I. INTRODUCTION .................................. 1
1. Purpose
2. Operational Definitions
3. Assumptions
4. Organization of the Study
II. SURVEY OF CURRENT KNOWLEDGE...................... 11
1. Selection of Engineers and Scientists
for Technological Study or Work
2. Managerial Selection in Industry
3. Clinical Studies of Management Success
4. Studies by Grimsley and Jarrett
III. RESEARCH DESIGN AND METHODOLOGY..................29
1. Matched Group Design
2. Study Group Characteristics
3. Research Variables
4. Hypotheses
5. Statistical Methods
IV. RESEARCH RESULTS.................................47
1. Differences Between MRL Groups
2. Discriminating Variables
3. Relation of Psychometric Scores to Age
4. MRL II Group's Similarities to MRL I
and MRL III Groups
5. Impact of Biographical Data on Discrimi
nation Between MRL Groups
6. Other Biographical Factors
Chapter
V. DISCUSSION AND CONCLUSIONS ....
1. Engineers and Scientists as
Managerial Resources
2. Profiles of MRL Groups
3. The Matched Group/Discriminant
Analysis Method
4. Test Scores and Age
5. Summary
APPENDIX A
♦
PSYCHOMETRIC TEST DESCRIPTIONS ....
Page
71
. 87
BIBLIOGRAPHY 104
LIST OF TABLES
Table Page
1. SOURCE OF SUBJECTS BY INDUSTRY .................. 8
2. TEST AND BIOGRAPHICAL DATA M E A N S ..................49
3. SUMMARY OF SIGNIFICANT DIFFERENCES
BETWEEN MRL GROUPS................................ 51
4. COMPARISON OF PREDICTED AND ACTUAL DIRECTION
OF TEST VARIABLE CORRELATION WITH
MRL G R O U P .................................. 54
5. CORRELATION BETWEEN AGE AND TEST SCORES........... 59
6. COMPARISON OF DISCRIMINANT ANALYSIS RESULTS
USING TEST AND BIOGRAPHICAL DATA WITH
TEST DATA ONLY.....................................64
7. NON-INTERVAL SCALE BIOGRAPHICAL
DATA SUMMARY.......................................66
v
CHAPTER I
INTRODUCTION
Science and technological change become increas
ingly more important to man and society with each passing
day. Therefore, both the private and public sectors of
our economy have found it desirable and in many cases even
necessary that more and more managerial talent be recruit
ed from the vast pool of engineers and scientists involved
in the development of this technological change.-^- Unfor
tunately, those qualities that contribute to achievement
in engineering and scientific areas do not always contrib
ute to the ability to deal successfully with increasing
managerial responsibilities.
Engineers and scientists spend the major part of
their educational and early job years developing their
technological competence. When an engineer or scientist
is promoted to the first level of management, the most
2
important criterion is usually past performance. In some
^Alvin Toffler, Future Shock (New York: Random
House, Inc., 1970) Chapter 2.
^Allen Slusher, James Van Dyke, and Gerald Rose,
"Technical Competence of Group Leaders, Managerial Role,
and Productivity in Engineering Design Groups," Academy
of Management Journal 15, 2, (June, 1972) 197-205"!
cases the results have been excellent, with the engineer
or scientist moving successfully to the very top of the
management ladder. However, in other cases, the results
have been disastrous, both for the firm and the individual.
1. Purpose
Since many engineers and scientists may not be
capable of effectively handling managerial responsibility,
it would seem beneficial to be able to identify those who
do possess the set of personal characteristics with great
est potential for assuming managerial positions. Thus,
the purpose of this study was to determine which set of
personal factors, if any, are related to potential for
attainment of managerial responsibility by engineers and
scientists. A most practical and feasible method to accom
plish this purpose was to analyze mental ability test
scores, self-descriptive inventory scores, and biographi
cal data items of engineers and scientists to determine
if significant differences existed between subjects who
had attained different levels of managerial responsibility.
This research is significant because it has iden
tified a set of readily obtainable variables or factors
which are related to potential for attainment of manage
rial responsibility among the increasingly important group
of technologically trained personnel in our society. This
information may be utilized in a variety of ways to assist
2
an organization select, train, and promote those engineers
and scientists with greatest managerial potential. Addi
tionally, it is believed that the results of this research
may provide some guidance for modification of current
education and training programs of potential managers.
2. Operational Definitions
Cronbach defines two distinct approaches to the
study of human behavior.^ One is the experimental method
in which an experimental treatment is imposed on the sub
jects and observation of the differences in behavior is
made and analyzed. The second approach is the correlatiPB-z
al (or differential) method which focuses on the dimensions
of behavior which already exist in nature and along which
individuals differ. Because of practical problems which
would require significant amounts of time and resources to
do an experimental study to identify factors related to
potential for attainment of managerial responsibility, the
differential method was used for this study.
This approach utilized an existing data bank con
taining mental ability test scores, self-descriptive inven
tory scores, and biographical data for a large number of
individuals who had been tested for promotions or new posi
tions during the 15-year period from 195 7 to 1972. From
O
Lee, J. Cronbach, "The Two Disciplines of Psycho1-
ogy," American Psychologist 12, (1957) 671-684.
3
these data the subjects for this study were selected.
Before going any further in the description of this inves
tigation, several terms of key significance must be defined.
Engineers and Scientists. For purposes of this
study engineers and scientists are defined as individuals
who have earned an undergraduate degree from an accredited
institution of higher education in one of the following
scientific or engineering disciplines:
1. Aeronautical Engineering 7. Mechanical Engineering
2. Chemical Engineering 8. Mathematics
3. Chemistry 9. Metalurgical Engineering
4. Civil Engineering 10. Metalurgy
5. Electrical Engineering 11. Mining Engineering
6. Industrial Engineering 12. Physics
In the data base available for this research 1,144 individ
uals were identified as engineers or scientists in accord
ance with the above definition.
Managerial Responsibility Level. The subjects iden
tified as engineers and scientists were further classified
by the level of managerial responsibility that they had
attained at the time they were tested. For purposes of
this grouping three Managerial Responsibility Levels
(MRL’s) were defined as follows:
MRL I -- Having complete general responsibility
and decision-making authority for all
functional areas of a firm or a major
profit center within a firm. (Executive
level.)
MRL II -- Having broad responsibility and decision
making authority within at least one
functional area of a firm. (Middle
Manager level.)
MRL III -- Having responsibility and decision
making authority in only a single tech
nical area. (Staff Specialist and
Technical Supervisor level.)
Of the 1,144 engineers and scientists, 84 were classified
in MRL I, 445 in MRL II, and 615 in MRL III. In classify
ing potential subjects by MRL, the level of managerial
responsibility attained prior to testing was used as the
best available measure. In all cases this information was
obtained from the subject's own written report of his work
history. In many instances, and in almost all cases in
volving higher level managers, resumes and reports from
executive search firms, industrial psychologists' reports,
and data from prior employers were available For each
potential subject the entire work history was examined in
order to avoid giving too much weight to the most recent
^The researcher's fifteen years of experience in
industry in a variety of engineering and managerial posi
tions was also quite useful in the identification of the
MRL of potential subjects.
5
position that may have been held only a short period of
time.
Matched-Group Design. A matched-group design was
used in this study because it appeared to offer a simple
method of controlling certain variables which would other
wise contaminate the results obtained. The approach used
was a variation of the traditional "matched group" experi
mental design in which subjects are matched on variables
C
that are correlated with the measured variables. Thus,
final selection of subjects for each MRL group was accom
plished by matching for age, education, and date tested.
Matching for age was within ^1 year. Matching for test
-f
date was within -2 years. Matching for education was
accomplished by matching for area of undergraduate degree.
Where exact degree matching was not possible in cases
where age and test date could be satisfactorily matched,
then degrees which were considered almost equivalent were
used. For example, in several cases a BSME was matched
with a BSAE since the requirements for both degrees are
quite similar.
Starting with the 84 MRL I potential subjects, a
match was attempted for each in MRL II and MRL III. As a
result of this three-way matching procedure 50 of the
MRL I subjects were matched with counterparts in both the
^J. P. Guilford, Fundamental Statistics in Psy
chology and Education, Fourth Edition (New York: McGraw-
Hill Book Company, 1965) 164-65.
MRL II and MRL III groups. Therefore the subjects for
this study consist of three matched groups of 50 subjects
each.
Subjects. The 150 engineers and scientists studied
were selected from among 1,144 male candidates for key
managerial or staff positions with a large multi-industry
conglomerate firm. The subjects were tested by an indus
trial psychologist and completed an eight-page biographical
date form as a result of their being considered for a new
position or an internal promotion. The subjects came from
109 different companies geographically dispersed throughout
the United States. The majority of subjects were from
organizations in industries such as electronics, heavy
manufacturing, aerospace, chemicals, basic metals, comput
ers, research and development, and construction. However,
other industries such as television, hotels, food proces
sing and distribution, consumer products, automotive
products, and consulting were also represented. While
accurate classification by industry was difficult because
many of the organizations were conglomerates and others
produced goods and services for diverse markets, Table 1
gives some indication of the types of organization from
which the subjects came.
3. Assumptions
Due to the nature of this study and in adherence
7
TABLE 1
SOURCE OF SUBJECTS BY INDUSTRY
INDUSTRY
NUMBER OF
SUBJECTS
Aerospace 47
Heavy Manufacturing 29
Electronics 29
Basic Metals 9
Computers 8
Chemicals 8
Research 7
Construction 4
Automotive Parts 3
Food Processing and Distribution
Television, Consumer Products,
2
Hotel, and Consulting 4
Total 150
8
to a criterion of "reasonableness” in the expenditure of
resources for data gathering and subject matching, several
assumptions were made.
A basic assumption in this study is that engineers
and scientists are those who have completed undergraduate
study of engineering or a "hard" science. Obviously, this
is a very limited definition and excludes a large popula
tion of those who have engaged in engineering or scienti
fic work although not in possession of a bachelor's degree
in that area. However, this assumption does allow the
consideration of a majority of the engineering and
scientific population and simplifies the group matching
process.
Another assumption was that a specific degree
earned at one school was equivalent to the same degree
earned at another school. This assumption was made because
the matching could not have been accomplished without it.
Furthermore, it was felt that in most cases after the entry
level job and certainly by the third or fourth job the
school where the subject's degree was earned was not a
significant factor.
r
4. Organization of the Study
The remainder of this dissertation is divided into
four chapters. Chapter II is a survey of current knowledge
which reviews the literature related to selection of
9
engineers and scientists for technical work or study,
methods for selection of managers, and studies of manageri-
al success.
Chapter III is a description and discussion of the
research design and methodology including a detailed
description of subject selection, matching, testing pro
cedures, and biographical data inputs. This chapter also
includes a discussion of the research design and the
methods of multivariate analysis used.
Chapter IV presents the information generated from
the data and its statistical significance.
Chapter V includes the conclusions drawn from the
study and a discussion of the practica1,significance of
the results.
10
CHAPTER II
SURVEY OF CURRENT KNOWLEDGE
Selection of personnel for various jobs and levels
of managerial responsibility has been a classic difficulty
for many years. The problem may become even more acute
with the effects of rapidly changing technology on our
institutions and organizations. For this reason investi
gators have sought and are continuing to seek knowledge,
understanding, and methods for making these decisions more
effectively.
An important aspect of managerial effectiveness is
leadership capability. Recent research related to leader
ship has resulted in three theories of leadership whose
propositions have been subjected to extensive empirical
testing: trait theory, behavioral theory, and situational
theory.
Trait theory proposes that there are a number of
identifiable traits of successful leaders and managers and
that these traits differentiate the successful from the
unsuccessful leaders. Behavioral theory holds that suc
cessful leaders and managers may be best characterized by
patterns of behavior rather than by individual traits.
11
The situational theorists hold that leadership can only be
explained in terms of the interaction between the manager
and the many variables in the work situation. For a com
prehensive description of these three theories and their
supporting research, the reader is referred to Chapter 16
of Filley and House, Managerial Process and Organizational
Behavior, Scott, Foresman and Company, 1969.
The objectives of this research were not concerned
with leadership in general, but with the attainment of
increasingly broad managerial responsibilities within the
corporate environment. There are no arguments with either
behavioral or situational theories. To the contrary, both
concepts are fully accepted. However, in this study the
situation was relatively fixed and considered a constant
while behavior of the subjects was used to place them in
the MRL groups. Thus, it was the researcher's objective
to measure trait differences which are correlated with
different levels of leadership and managerial behavior in
the corporate environment. It was felt that if successful
managers in various corporate organizations had similar
traits, and these were different from the traits of less
successful managers, it would add significantly to the body
of knowledge in the trait theory area.
The literature of interest to this study seemed to
fall into three categories. First, there are reports of
studies and research related to selection of engineers and
12
scientists for technological study and work. Second, there
are those studies related to managerial selection criteria
in industry. Third, there are the clinical research
studies of managerial success.
1. Selection of^Engineers and Scientists
f°r Technological Study or Work
Much of the interest in engineering and scientific
talent has focused on identification and measurement of
creativity and related concepts.^ However, there have been
some studies related to prediction of student success in
college and in entry-level jobs.
One of the most important research developments is
the Minnesota Engineering Analogies Test (MEAT). Origi
nally designed by Dunnette to select engineers who could
best meet the requirements for graduate studies, MEAT was
subsequently revised to be used as an instrument to dis
criminate between working engineers.7 Although MEAT is
basically a general mental ability test, it does combine
measurement of intelligence with prior engineering school
achievement. This is accomplished by use of verbal anal
ogies requiring abstract reasoning, with the subject matter
^C. H. Lawshe and Michael J. Balina, Principles of
Personnel Testing, Second Edition (New York: McGraw-Hill
Book Company, 1966), 230.
^Marvin D. Dunnette, ’’ The Minnesota Engineering
Analogies Test: A New Measure of Engineering Ability,
Journal of Personal Administration and Industrial Relations,
i,'7 T95*y"i-io.--------------------------------------------------------
13
being basic engineering principles.
Dunnette found that MEAT discriminates not only be
tween seniors and graduate students, but also between
master’s degree and doctor's degree engineers. To his
surprise, Dunnette also found that fast workers on MEAT
were just as accurate as slow workers. MEAT has also been
found to discriminate between engineers engaged in pure
research from those engaged in other activities such as
development, production, or sales. Researchers score high
er on the test than do other types of engineers.
/
Another test used to predict potential success in
engineering school is the Employee Aptitude Survey (EAS).
One study using EAS was conducted at the University of
Q
Southern California School of Engineering. Two separate
samples were drawn from the 1956 and 1957 entering fresh
man classes. A predictive equation was developed from the
first sample and then cross validated on the second sample.
A composite score for the EAS was computed for each student
in the first group and a multiple correlation (validity
coefficient) of .83 was obtained between the composite EAS !
score and grade-point average obtained in the first year
of college. The cross-validation utilizing the next year's
class upheld the results of the original group with negli
gible "shrinkage" (R=.80).
# •
O
This study was performed by Glenn A. Foy, Associ*-
ate Professor of General Engineering, University of
Southern California.
These results reflect a forecasting efficiency in
education which is unusual. This is particularly signifi
cant considering that less than an hour of actual test time
per student is required for the EAS. Test 2 (Numerical
Ability) in particular, makes a significant contribution to
the prediction equation. For a complete description of the
EAS see Appendix A.
A similar study conducted at Los Angeles City
College (L.A.C.C.) attempted to develop a predictive in
strument that would take no longer than thirty minutes of
actual testing time.® For this purpose five of the EAS
tests were selected and a validity coefficient of .60 was
obtained between a pass-fail criterion and a composite
score from the five tests. A comparison of the results of
both studies indicates that at both U.S.C. and L.A.C.C. the
Numerical Ability Test was the best single predictor of
success in freshman engineering.
The use of mental ability tests to predict success
of engineers on the job was investigated by Meyer at
General Electric.'*"® His study of 164 engineers used a long,
untimed test of general mental ability. The results
®This study was conducted jointly by the staff of
Psychological Services, Inc. of Los Angeles and William
R. Lennox, Instructor in Engineering and Psychology, Los
Angeles City College.
■*"®Herbert H. Meyer, A Research Study of the Use of
Tests and the Interview for Evaluating Technical Personnel,
(New York: General Electric Company, 1954).
15
i indicated that the mental ability test was useful in selec-
i tion of engineers for technical tasks only to the extent
j
I that low scores did predict poor performance. However,
i
! Meyers found that high scores did not predict success. He
i
' concluded, therefore, that above a certain minimum mental
»
! ability level required to perform the technical job other
I factors were more important in determination of success.
i
I
i He found that temperament measures were among these factors,
i
j
jMeyer1s study indicated that good results were obtained
; with a combination of the Thematic Apperception Test (TAT)
t
! and the Group Rorschach Test. This was unusual since pro-
i
i jective tests of this nature have seldom been found of
jvalue for such use.H In fact, Meyer himself points out
| that where projective tests are used the skill of the test
; analyst is a very critical variable as far as validity of
. I
, predictions are concerned.
The preceding material in this section was mainly
concerned with selection of personnel for technical train
ing and work. Another decision that is significant is the
j placement decision. In other words, once a person has been
i
i selected by an organization how can his value to the organ-
»
i
j ization be maximized? In which job will he have the high-
j est probability of success? This subject is complex, for
• ...
f
i
! ..... H-Lawshe and Balma, Principles of Personnel
I Testing, 233.
!
i i 6
certain skills, abilities, and other characteristics may
differentiate between two occupational groups and yet not
be a valid predictor of "success" in either one.
This is illustrated well by Kirkpatrick's compre
hensive study of 244 engineers each employed for over one
12
year by a nationally known manufacturing company. The
subjects were given a battery of tests and were also rated
on their job performance by their superiors. This study
was concerned not only with test prediction of success in
each area, but also test differences between job types.
Kirkpatrick found little difference between factory, serv
ice engineering, sales and application engineering groups.
These were therefore combined into a single group that was
compared to research and development (R & D) engineers. It
was found that mental ability measures of mathematical
formulation, spatial visualization, and mechanical compre
hension and personality measures of sociability and friend
liness combined to discriminate significantly between these
two groups. These test scores could be used to predict
which group a subject belonged to and therefore could be
used for placement purposes.
Further study by Kirkpatrick of job success showed
that this could not be predicted from the same test scores.
1 9
James J. Kirkpatrick, "Validation of a Test Bat
tery for the Selection and Placement of Engineers,"
Personnel Psychology 9, (1956), 211-227.
17
Thus, a significant result of this study is the fact that
because a test is valid for placement does not mean that it
is valid for success, or vice versa. Placement and success
prediction are independent objectives and must be individ
ually determined.
2. Managerial Selection in Industry
Perhaps the most widely discussed and extensively
validated study of managerial selection in industry is the
Early Identification of Managerial Potential (EIMP) study
by Standard Oil Company of New Jersey (SONJ).^ After
initial validation, the statistical equations developed at
SONJ were applied to a number of other subsidiary companies
in the Standard Oil organization in attempts to determine
if managerial success can be measured and how to identify
employees with high management success potential.
The study involved the use of 443 managers of SONJ
and five of its affiliate companies as subjects. The sam
ple included managers from many different functional areas
including marketing, research, production, accounting, and
13
This is an excellent example of a long-term staff
study with many researchers taking part. Some of the most
significant contributors were C.P. Sparks, A.M. Munger,
Carl H. Rush, Paul F. Ross, Douglas Fryer, McE Trawick,
Paul C. Baker, Tredway Parker, Henry Laurent, and E.R.
Henry. The study is described in EIMP (Early Identification
of Management Potential), Published by the Standard Oil
Company of New Jersey, Social Science Research Division,
Employee Relations Department, and is available from them
on request.
18
staff specialties such as medicine and law. This was done
because SONJ management wanted to identify those employees
with potential for general management positions rather
than pinpointing potential for narrowly oriented specific
functional areas. This was an important difference from
many of the other inquiries into prediction of managerial
success.
Each subject was given a lengthy battery of tests
and completed an extensive biographical survey covering
home and family background, education, vocational planning,
finances, hobbies and leisure activities, health history,
and social relations. The tests included mental abilities
such as verbal ability and inductive reasoning, manage
ment judgment^ attitudes, and personality measures.^
Test scores were correlated with the ratings of the indi
vidual subjects on an overall managerial success index
1 f i
developed by the SONJ researchers. The subjects were
randomly divided into subgroups of 222 and 221 each and a
■^Management judgment was tested by providing a
number of different human relations situations which the
subjects had to evaluate and then choose an effective
course of action.
"^Personality measures were obtained from the
Guilford-Zimmerman Temperament Survey. This is one of the
instruments used in the study reported herein.
■^The index of managerial success included position
level, salary history, and effectiveness ranking by higher
company officials who had observed the behavior of the
managers being ranked.
19
double cross-validation was used to assure stability of the
relationships discovered. Scoring keys were developed from
each subsample and cross-validated on the other sample.
From these data the SONJ researchers developed a
single combined score from the test and questionnaire
materials which had a correlation of .70 with the success
index. Unfortunately, since the two special scoring keys
(managerial success and test keys) are understandably
secret, it is difficult even to speculate about the spe
cific nature of the qualities contributing to managerial
attainment or success at SONJ. However, the general method
used does seem valid and was used to some extent as a model
for the research reported in this study of managerial
attainment by engineers and scientists.
Another large-scale study of personal characteris
tics that are related to managerial attainment was conduc
ted by the Industrial Relations Center of the University
of Minnesota.^ A sample of 452 managers from thirteen
firms operating in the state of Minnesota were selected.
The subjects represented various areas of managerial activ
ities such as manufacturing, finance and insurance, public
utilities, agricultural products, and wholesale trade.
The study dealt primarily with middle managers from all
^T.A. Mahoney, T. H. Jerdee, and A. N. Nash,
"Predicting Managerial Effectiveness," Personnel Admini
stration 26, (1963) 21.
20
functional areas.
Managerial effectiveness was determined in essen
tially the way used in the SONJ study described above.
The subjects were administered a battery of tests to
measure mental ability, vocational interest, personality
characteristics, and empathy. They were also requested to
complete a biographical questionnaire which described their
education and job experience, activities, and personal and
family circumstances prior to age twenty-five. The sample
of subjects were randomly placed into two equal groups of
226. A scoring system based upon test results was devel
oped for each of the two groups and cross-validated on the
managers in the other group. Of 98 predictors tested in
this study, 18 showed statistically significant (.10 level)
relationships with the managerial effectiveness rankings.
On the basis of these findings the investigators charac
terized the more effective manager as follows:
A more effective manager tends to have interests
that are similar to other men in the business field
and tends not to have interests similar to men in
agriculture and skilled trades. On the average, he
tends to be somewhat more intelligent and more domin
ant than less effective managers. His biographical
background shows that he has had more educational
training and was more active in sports and hobbies as
a young man. Also, his wife has had more educational
training and has worked less after marriage.18
The validities obtained in this study were somewhat
. 18Ibid.
21
lower than those obtained in the SONJ study. Probably the
validities obtained in this study were lower and more
realistic because of the type of data utilized and the
fact that many different companies were represented in the
sample population. The bibliographical form used by the
Minnesota researchers was much less broad in revealing
descriptive information than the background survey used in
the SONJ study.
One of the most comprehensive research efforts
using biographical data only was a study of American
Chamber of Commerce executives. An eleven-page biographi
cal questionnaire was developed by Kirkpatrick which
covered early family history, family background, education,
employment history, military service, social information,
and physical condition.^ . Over 600 responses were received
from a mailing of the questionnaire to 1,300 Chamber
executives.
An evaluation of the 600 respondents by their
superiors was used to develop a scoring system to predict
above average executive performance from the biographical
data. A cross-validation of the scoring system yielded a
point biserial correlation with the criterion function of
.56.
James J. Kirkpatrick, "How to Select a Chamber of
Commerce Executive,” Journal of American Chamber of
Commerce Executives, 10, (1961) 2-6.
22
A five-year follow-up study was conducted using
current salary as an estimator of managerial effectiveness
of the executives who had completed the questionnaires.
"High salary" managers were matched for age and chamber
size with an equal number of "low salary" managers and
their biographical scores were compared. The mean score
for the high salary group was about two standard deviations
above the mean score for the low salary group. Unfortu
nately, the actual content of the significant items making
up the biographical score is secret. However, it was
stated that it was similar in content to the items found
most useful in the SONJ study. The "successful" Chamber
executive had a middle-class socio-economic background,
had a stable family and happy childhood, was well educated,
active in extracurricular activities and had leadership
roles in many of them, emphasized communications skills,
and entered Chamber of Commerce activities prior to age
thirty-five.
These Chamber of Commerce studies are significant
for several reasons. First, they utilized a behaviorally
based definition of management effectiveness to define the
bases for global rating obtained from senior Chamber Execu
tives. Second, managers differing in attainment of
success were matched for age and job experience (i.e., the
opportunity to achieve success). And finally, the pre
dictive usefulness of the biographical data technique
23
was established by a follow-up study.
3. Clinical Studies of Management Success
In researching the literature related to actual
decision practices of industrial firms and government agen
cies in the selection of managerial talent, it was found
that such decisions most often involve a composite clinical
strategy. Even when sets of predictor variables have been
combined in elaborate statistical regression equations, cer
tain other information (e.g., appraisal data, career his
tory, availability, and age) have been used to supplement
that provided by the variables contained in the equations.
Since the clinical approach is, in practice, used so widely,
it seems appropriate to discuss its relative accuracy in
this section.
The most exhaustively reported clinical studies of
managerial effectiveness are those carried out by the Psy
chological Research Services (PRS) of Case Western Reserve
University. The PRS has, for a number of years, been
assessing persons being considered for responsible jobs in
business and industry. Follow-up studies of a number of
these persons to determine their relative job effectiveness
have been conducted and reported in several articles.
^Among the many articles describing the PRS re
search are J. T. Campbell, '’ Assessment of Higher Level
Personnel. . . . . I. . Background and Scope of the Research," Per
sonnel Psychology 15, (1962) 57-62, and J. T. Campbell,
et al.~ ’ ’ Assessment of Higher Level Personnel. II. Valid-
ity of the Overall Assessment Process,"Personnel Psychol
ogy 15, (1962) 63-74.
24
Each candidate was given a battery of psychological
tests including the American Council on Education Intelli
gence Test, the Cooperative Reading Test, the Guilford-
Zimmerman Temperament Survey, the Edwards Personal prefer
ence Schedule, the Kuder Preference Record, and projective
instruments such as the Thematic Apperception Test and the
Worthington Incomplete Sentence Test. Additionally, two
psychologists having no knowledge of the candidate's test
results, interviewed and rated the candidates. The pro
jective instruments were examined by another clinical psy
chologist who also completed a set of ratings without
seeing the candidate. All of this information was collated
by a report writer for the client firm. Ratings reported
were based on (1) objective test results only, (2) psychol
ogist's written report only, and (3) full and complete
information. Eight person- or trait-oriented dimensions
rather than job-oriented dimensions were used for all of
the ratings. These dimensions were: social skills,
persuasiveness, leadership, intellectual capacity, crea
tiveness, planning, motivation and energy, and overall
effectiveness.
At least six months after these ratings, global
effectiveness ratings on the job were obtained from super
visors of those candidates that had been hired. The cor
relations between the assessment procedures and the super
visor's ratings were good considering the many
25
extrapolations between applicant's responses and the be
havior ratings and predictions. (The median correlation
was .25 between supervisory rating and the composite of all
clinical evaluation data). One unfortunate item was that
the researchers did not report results separately for man
agerial and nonmanagerial candidates. Also it is not clear
in this case how much effect the written reports had on the
supervisor's global effectiveness ratings.
Another clinical study of managerial effectiveness
91
was performed for the 3M Company by Dunnette and Kirchner.
The researchers validated the three clinical hypotheses
that more effective managers should: (1) be more intelli
gent, (2) have broader interests, and (3) have "stronger"
personalities than less effective managers. To do this
they administered a battery of tests including the Miller
Analogies Test (MAT), the Wechsler Adult Intelligence
Scale (WAIS), the Strong Vocational Interest Blank (SVIB),
the California Psychological Inventory (CPI), and the
Edwards Personal Preference Schedule (EPPS) to 26 sales
managers. The overall correlation coefficient was .61
between the criterion and the test results. The criterion
or global effectiveness of each of the 26 managers was
determined by comparisons and rankings made by the general
21
Marvin D. Dunnette and W. K. Kirchner, "Valida
tion of Psychological Tests in Industry," Personnel
Administration 21, (1958), 20-27.
26
manager and vice president of each subject's product
division.
Even though this study was based upon a small sam
ple of sales managers it seems significant in that it
demonstrated that a clinical combination of tests could be
used to validate hypotheses based upon characteristics
believed to be important for successful managers. The re
searcher's methods were clearly identified and could be
used by others interested in replicating the clinical pro
cesses. This is a characteristic which most other clinical
studies do not possess.
4. Studies by Grimsley and Jarrett
In late 1969, Dr. Glen Grimsley of the University
of Southern California and Dr. Hilton F. Jarrett of
California State University at Long Beach began a long
range research program to develop better understanding of
factors contributing to managerial success. The research
described herein is a continuation of those studies and
looks at the specific category of managers that develop
from engineering and science backgrounds.
In the first published results of their studies,
Grimsley and Jarrett report that there were significant
differences in some mental ability test scores between top
22
executives and middle managers. There were also several
22cien Grimsley and Hilton F. Jarrett, "The Re
lation of Past Managerial Achievement to Test Measures
Obtained in the Employment Situation,” Personnel Psychol
ogy 26, (1973) 31-48.
personality measures in which significant differences were
reported. A comparison of these results and those from
the research described herein is presented in Chapter IV
of this paper.
Much of the research described in this chapter in
volves the use of various tests (aptitude, ability,
personality, etc.) related to the measurement of managerial
traits. Therefore, the reader is refered to Lawshe and
Balma, Principles of Personnel Testing, McGraw-Hill, 1966,
for further comprehensive coverage of testing concepts,
trait measurement, and test application areas.
28
CHAPTER III
RESEARCH DESIGN AND METHODOLOGY
The research design and methodology were selected
to utilize a rich source of data available through the
courtesy of Professor Glen Grimsley of the University of
Southern California. As a result of his contacts with
industrial firms during more than twenty years of work as
a consultant, specializing in executive selection and
evaluation, he had assembled a data base of records of
thousands of individuals now employed in positions ranging
from first level supervision and staff specialist to top
level general management. Each individual record consists
of mental ability and self-descriptive inventory test
scores, biographical data forms, and a report of an exten
sive interview by an industrial psychologist. From this
data base the subjects for this research were selected.
1. Matched Group Design
The matched group design used in this study has
been described briefly in Chapter I and has been used by
Grimsley and Jarrett in their study.^3 However, this study
^Ibid .
differs from others in that three matched groups were used
rather than the two-group design utilized in most other
similar studies. The matching criteria were: 1) major
field of education within engineering or the other "hard”
sciences, 2) age, and 3) date subjects were tested. The
matching process for these three variables yielded fifty
sets of three-way matches from an initial data base of 84
MRL I, 445 MRL II, and 615 MRL III subjects.
To eliminate bias in the test results, all poten
tial subjects judged to have serious language and/or cul
tural handicaps (those for whom English was not their first
language) were eliminated from consideration in each of the
three groups. Next, a match was made on educational
specialization. Then the matching for age and test dates
were made. These were kept within 11 and -2 years respec
tively. The means and standard deviations of the ages of
the three groups were as follows:
MRL I MRL II MRL III
Mean 41.46 41.56 41.48
S.D. 4.72 4.74 4.92
The mean deviations in test dates from MRL I were:
MRL II MRL III
-.01 years -.38 years
These results would seem to indicate the adequacy of the
matching process.
30
2. Study Group Characteristics
All subjects were male due to a lack of adequate
j female representatives in the data base. The MRL I group
ranged in age from 33 to 52. Their direct salaries ranged
; from $13,000 to $90,000 (mean $37,000) and all were receiv-
f ing additional compensation in the form of stock options
i and/or bonuses. Thirty-nine had degrees in one of the
engineering fields and eleven had degrees in either phys-
! ics, mathematics, or chemistry.
i
I The MRL II group ranged in age from 34 to 52.
| Their direct salaries ranged from $10,000 to $31,000 (mean
i
! $21,000) and 34 per cent were receiving additional compen-
!
! sation in the form of bonus, a share in profits, and/or
I
! stock options. Thirty-nine had degrees in one of the en-
!
! gineering fields and eleven had degrees in either physics,
; mathematics, or chemistry.
i The MRL III group ranged in age from 33 to 55.
!
Their direct salaries ranged from $9,000 to $22,000 and
i
i none were receiving any additional compensation. Thirty-
J eight had degrees in one of the engineering fields and
twelve had degrees in either physics, mathematics, or
i
I chemistry.
I
| 3. Research Variables
| The test variables utilized in this study were
j obtained from six standard psychometric tests of mental
; skills and personality self-descriptive inventories widely
used in personal assessment of individuals. Each test
score measured an individual's performance on a particular
well defined variable. Eight test measures of mental
ability and thirty-four test measures of personality were
obtained for each subject.
Caution must be taken in analyzing these test
results. The nominal abbreviations for these variables
may be easily misconstructed by those not thoroughly
familiar with the tests. Only the test manual's specific
definition of each variable should be used for interpreta
tion. (A description of the test variables is given in
Appendix A.) The abbreviated terms are terms common to
lay use in everyday life, but have special and quite
specific meanings in test use. Several of the tests use
highly similar or identical abbreviations for constructs
which are differently defined and derived.
The following is a list of the tests used and the
nominal abbreviations of the variables measured by each.
\
Employee Aptitude Survey (EAS)
Verbal Comprehension (EAS-1)
Numerical Ability (EAS-2)
Visual Speed and Accuracy (EAS-4)
Space Visualization (EAS-5)
Numerical Reasoning (EAS-6)
Verbal Reasoning (EAS-7)
32
Word Fluency (EAS-8)
Symbolic Reasoning (EAS-10)
Kuder Preference Record-Vocational (K)
Outdoor (K-0)
Mechanical (K-l)
Computational (K-2)
Scientific (K-3)
Persuasive (K-4)
Artistic (K-5)
Literary (K-6)
Musical (K-7)
Social Service (K-8)
Clerical (K-9)
Study of Values (Allport, Vernon and Lindzey)
Theoretical (SoV-T)
Economic (SoV-E)
Aesthetic (SoV-A)
Social (SoV-S)
Political (SoV-P)
Religious (SoV-R)
Guilford-Zimmerman Temperament Survey
General Activity (GZ-G)
Restraint (GZ-R)
Ascendance (GZ-A)
Sociability (GZ-S)
(SoV)
(GZ)
33
Emotional Stability (GZ-E)
Objectivity (GZ-O)
Friendliness (GZ-F)
Thoughtfulness (GZ-T)
Personal Relations (GZ-P)
Masculinity (GZ-M)
Gordon Personal Inventory (GPI)
Cautiousness (GPI-C)
Original Thinking (GPI-O)
Personal Relations (GPI-P)
Vigor (GPI-V)
Gordon Personal Profile (GPP)
Ascendancy (GPP-A)
Responsibility (GPP-R)
Emotional Stability (GPP-E)
Sociability (GPP-S)
Each variable measurement in the above tests is a
summational-type score based upon the sum of counted
responses in a particular category. The GZ^ GPI^ and
o /
J. P. Guilford and Wayne S. Zimmerman, Manua1:
Guilford-Zimmerman Temperament Survey, (New York: Sheridan
Supply Co., 1949).
25Leonard V. Gordon, Manual; Gordon Personal
Profile, (New York: Harcourt” Brace & World, Inc., T963).
34
GPP26 are factor-analytically constructed tests. The
variables in these tests are theoretically independent
within each test and show relatively low correlation
between each other. The EAS^ is a multi-battery of
independent tests. By factor-analytic methods its vari
ables are shown to be relatively independent. The Kuder^
O Q
and SoV, however, are ipsative tests. Thus, a high score
on one variable necessarily results in some other score or
scores being lower. The result is that the variable raw
scores are not independent with the tests.
The measurement characteristics of these tests
indicate that they would most properly be classified as
ordinal scales. However, most psychometricians and other
users of these instruments have chosen to assume that the
variable measurements are "at least interval scale." This
is the assumption made for this study. Guilford has
described some studies using such data which have compared
^ L e o n a r d yt Gordon, Manual: Gordon Personal Pro
file , (New York: Harcourt, Brace & World, Inc., 1963).
2?Floyd l . Ruch and William W. Ruch, Employee
Aptitude Survey Technical Report, (Los Angeles: Psycho
logical Services, Inc., 1963).
^Science Research Associates, Inc., Administra
tor^ Manual, Kuder Preference Record, (Chicago: 1960).
29cordon W. Allport, Philip E. Vernon, and Gardner
Lindzey, Manual: Study of Values, (Boston: Houghton
Mifflin Company, 1970).
35
effects of ordinal-scale versus interval scale assump-
o 0
tions. Comparisons showed linear relationships for the
individual cases. Guilford suggests that if the researcher
could accept the logical base on which pair-wise scaling
was established, it should be possible to also accept the
equality of interval units for summation scores on the
same test.
Five of the six psychometric tests used in this
study are tests of personality traits. Faking of such
tests is always possible. Most tests of this nature use
the forced-choice method as a deterrent to faking. Since
all subjects used in this study took the tests with a
knowledge that their performance would be used in judging
them competitively against others for promotion or employ
ment at higher levels, it seems most likely that all would
be motivated to make their best impression. Such motiva
tion would most likely cause the subjects to answer in ways
which they thought were most appropriate and thus would be
biased toward their perception of the most acceptable
value-sets for the position for which they were competing
in so far as their self-images would allow. Since the
objectives of this study were concerned with differences
between MRL groups, rather than with individuals, it would
seem that such bias would aid the desired discrimination
analysis.
30j. p. Guilford, Psychometric Methods, (New York:
McGraw-Hill Book Company, 345).
36
The following is a list of the interval scale
biographical variables also used for analysis in this
study.
Variable No. Variable Name
104 Subject's age
106 Subject's age at first marriage
107 Recency of last marriage
108 Present wife's age at marriage
109 Number of children
115 Father’s education
116 Mother's education
122 Number of siblings
123 Number of brothers
124 Number of sisters
125 Education of brothers
126 Education of sisters
130 Subject's education
132 Time major changed
147 Number of jobs held
161 Number of advanced degrees
162 Times discharged or demoted
163 Times laid off
37
164 Times changed job to
better self
165 Times changed jobs for
health/location
166 Number of least liked
subjects
168 Number of publications
172 Number of types of
remunerat ion
173 Father's age when
subject born
174 Mother's age when
subject born
178 Wife's education
184 Age of subject at first
degree
These variables were obtained from the biograph
ical data form each subject was required to complete as
part of the testing process.
38
4. Hypotheses
The objective of this study was to gain greater
insight regarding the differences between engineers and
scientists who had attained different levels of managerial
'responsibility. Specifically, mental ability, personality,
_ m - - hi inn i ■ i - r n - i i ' " - ' * m m i — »L . 1 11 . ...^
and personal history factors were investigated. While this
study may be characterized as primarily exploratory and
descriptive, it is felt that if significant differences
were found between MRL groups, then it may be possible with
further research to develop predictive tools utilizing the
above factors.
Based upon preliminary findings by Grimsley and
Jarrett in this area the following hypotheses were formu
lated for testing by this research.
Hi -- There are significant differences in
mental ability test scores, personality
test scores, and biographical factors
between MRL groups.
H2 -- A small number of variables having the
most significant differences can be used
in combination to discriminate between
MRL groups.
H3 -- Correlation of test scores with age
(except mental ability scores) within
each MRL group will be small and will be
similar in all three groups.
H4 -- It will be most difficult to dis
criminate MRL II because subjects in
this group will be quite similar to
MRL I subjects on some variables and
more similar to MRL III subjects on
other variables.
While the Grimsley and Jarrett studies were of a
two-group design (top level managers and middle managers),
and this research design includes three groups, it is rea
sonable to assume that their results may be indicative of
results to be obtained from the three group design (MRL I,
II, and III) used in this study. Thus, the formulation of
Hi included expectation of either positive or negative cor
relation of specific test variables. The following EAS
variables were expected to be positively correlated with
MRL:
Verbal Comprehension (EAS-1)
Numerical Ability (EAS-2)
Visual Speed and Accuracy (EAS-4)
Space Visualization (EAS-5)
Numerical Reasoning (EAS-6)
Verbal Reasoning (EAS-7)
Word Fluency (EAS-8)
Symbolic Reasoning (EAS-10)
The following GZ variable were also expected to be posi
tively correlated with MRL:
General Activity (GZ-G)
Ascendance (GZ-A)
Sociability (GZ-S)
Emotional Stability (GZ-E)
Objectivity (GZ-O)
Friendliness (GZ-F)
Thoughtfulness (GZ-T)
Personal Relations (GZ-P)
Masculinity (GZ-M)
The GZ variable, Restraint (GZ-R) was expected to be nega
tively correlated with MRL. The following Gordon test
variables were expected to be positively correlated with
MRL:
Ascendancy (GPP-A)
Vitality (GPI-V)
Gordon variables expected to be negatively correlated
were:
Cautiousness (GPI-C)
Personal Relations (GPI-P)
The only Kuder variables expected to be positively cor
related with MRL were computational (K-2) and Persuasive
(K-4). Artistic (K-5) was the only Kuder variable expected
to be negatively correlated with MRL. The SoV variables
expected to be positively correlated with MRL were:
Economic values (SoV-E)
Political values (SoV-P)
The SoV variable expected to be negatively correlated with
MRL was Religious values (SoV-R) .
The formulation of H2 was based on the Grimsley and
Jarrett finding that, out of 44 test score measures, 13
were found to differentiate the middle from the top manager
groups at the .01 significance level. It is expected that
fewer significant variables will be found in this study due
to the fact that all subjects regardless of MRL groups are
engineers and scientists and can be expected to be more
similar in many of the measured variables than were the
Grimsley and Jarrett subjects.
The third hypotheses was based upon the fact that
among MRL II and MRL III subjects, age is an excellent
measure of the time spent in middle and lower level posi
tions. Grimsley and Jarrett found a very low positive
correlation between amount of middle and lower level manage
ment experience and test scores that were predictive of
managerial achievement. Their view, based upon considerable
research, is that, except on highly speeded ability tests,
manager's performance on tests administered in the employ
ment situation changes little with age and experience.
The formation of H4 was based upon the assumption
that subjects in MRL II were there because in some signifi
cant variables they were similar to MRL I subjects but in
other significant variables they were more like MRL III, sub
jects. Thus, the MTL II or middle manager group were truly
42
in the middle because they possessed some significant
characteristics of both the high level and low level groups.
A fifth hypothesis, not based upon the Grimsley and
Jarrett studies, was also formulated for testing in this
study.
H5 -- Biographical factors will not aid signifi
cantly in discrimination between MRL groups
when added to the psychometric variables.
The reasons for formulation of H5 is twofold. First, it
can be generally assumed that in the employment situation
biographical data supplied by the subject is not as reli
able as psychometric test scores. Often this is simply
due to lack of accurate recall by subjects. However, there '
is also the possibility that subjects applying for similar
positions who have had differing amounts of managerial ex
perience may view certain biographical data items with
differing, importance which in turn may vary the accuracy
of the responses. Reliability also is reduced by the fact
that many scales have few categories and are very ’’rough"
measures. Second, it was also felt that the significant
psychological traits or characteristics would be highly
correlated with biographical data. Thus, when given the
psychometric test scores (which were felt to be more reli
able in the first place), the biographical data would not
add significantly to the discriminant analysis results.
5. Statistical Methods
The processing and analysis of the test score and
interval scale biographical data utilized the Statistical
Package for the Social Sciences (SPSS).^ This powerful
set of data processing routines provided all of the
statistical tests and methods to test each of the five
hypotheses.
Testing of Hi was accomplished by the use of the
paired variable t-test to compute the means of the test
scores and biographical data items for the subjects in
each MRL group and also to compute the statistical signi
ficance of the differences between the means. The signifi
cance of differences between means of MRL I and MRL II,
MRL I and MRL III, and MRL II and MRL III were computed.
The multiple stepwise discriminant analysis func
tion of SPSS was used to test H2, H4, and H5. This sta
tistical processing method is one which identifies a subset
of variables which "best" discriminates between different
populations such as the MRL groups. Briefly, the process
is as follows: First, the variable for which the mean
values in the three groups are "most different" is identi
fied. This difference is measured by a one-way analysis
of variance F statistic and the variable with the largest
^Norman H. Nie, Dale H. Bent, and C. Hadlai Hall,
Statistical Package for the Social Sciences, (New York:
McGraw-Hill Book Company, 1970).
F value is chosen (or entered into the discriminant
subset). On successive steps, the process considers the
conditional distribution of each variable not entered given
the entered variables. Of the variables not entered, the
variable for which the mean values of the conditional dis
tributions in the three groups are "most different" is
selected as the next entering variable. This difference
is also measured by a one-way analysis of variance F sta
tistic. The stepwise process is stopped when no additional
variables significantly contribute to the discrimination
09
between the different groups.
This discriminant analysis process provides a
linear function of the observed X variables which has high
values when an observed subject belongs to one group and
low values when he belongs to the others. The procedure
followed, was to generate a system of three linear equa
tions, one for each MRL group. The discriminant functions
thus generated by the odd numbered subjects were validated
using the selected variables for the even numbered subjects
32
For a more complete discription of the stepwise
discriminant analysis method see A.A.Afifi and S.P. Azen,
Statistical Analysis: A Computer Oriented Approach,
(New York: Academic Press, 1972, 252) or Edward C. Bryant,
Statistical Analysis, Second Edition, (New York: McGraw-
Hill Book Company, 1966, 238).
45.
and vice versa. The output matrices from this process were
then given chi square tests to determine the level of sig
nificance of the discrimination (or prediction) power of
the generated discriminant functions.
This discriminant analysis process was used first
with both test scores and biographical data. It was then
run using only the test scores. A comparison of the re
sultant predictive power of the sets of discriminant func
tions was used to test H5.
Simple correlation analysis of test scores with age
was used to test H3. This method is the same as that used
in the Grimsley and Jarrett study.
46
CHAPTER IV
RESEARCH RESULTS
The data for this research came from the test
results and biographies of one hundred fifty graduate
engineers and scientists. All subjects were college
graduates and had been working in industry for at least ten
years and some as many as thirty years prior to being
tested. The subject population (all three MRL groups com
bined) were superior to the general male population in in
tellectual capability and were more similar to each other
in personal traits than 150 subjects selected from the
general male college population would be. This was to be
expected due to the subject selection process (as described
in Chapter III). Therefore, fewer differences in test
scores might be expected between the MRL groups. Thus,
those differences which were found were felt to be more
significant from a practical point of view than the purely
statistical significance may indicate.
1. Differences Between
MRL Groups
The means of the test scores and means of interval
scale biographical data for the three MRL groups are
47
presented in Table 2. The 42 test scores shown are the
raw score means for each MRL group. The t-test values
indicate the significance of the differences between MRL I
and the other two MRL groups. Of the 42 test scores,
seven were found to differentiate between MRL I and MRL II
at the .01 significance level, and five additional at the
.05 level (one-tail test).33 of the 42 test variables, 18
were found to differentiate between MRL I and MRL III at
the .01 significance level and six. more at the .05 level
(one-tail test).34
The 28 interval-scale biographical data items
yielded only one difference at the .01 level and one dif
ference at the .05 level between MRL I and MRL II. How
ever, there were eight .01 level differences and four .05
level differences between MRL I and MRL III.
A summary of significant differences between MRL
groups is presented in Table 3. A total of 14 variables
in all three categories were significantly different for
MRL I and MRL II subjects at the .05 level or better.
33xhe one-tail test was used because the signs of
the 12 significant differences were those expected. Tests
of 42 differences might be expected to yield two or three
significant at the five per cent level because of chance
differences alone.
^The one-tail test was used because the signs of
the 24 significant differences were those expected.
48
TABLE 2
TEST AND BIOGRAPHICAL DATA MEANS
Variable
MRL Group Mean t-Test
I II III I-II I-III
Test Scores
EAS-1 Verb.Comp. 25.74 24.88 23.76 1.58 3.01**
2 Num. Ability 20. 74 20.08 19.14 1.17 2.68**
4 Vis.Speed 57.22 51.14 45.92 1.47 2.87**
5 Space Visual 34.22 32.86 31.90 0.79 1.39
6 Num.Reason. 14.52 13.64 13.04 1.52 2.83**
7 Verb.Reason. 20.00 17.34 16.12 3.83** 5.79**
8 Word Fluency 54.84 47.80 46.68 2.99** 3.04**
10 Sym.Reason. 16.63 15.24 13.48 1.11 2.49**
GZ-G Gen.Act. 24.10 21.72 17.62 3.04** 7.28**
R Res traint 20.10 20.72 20.56 -0.93 -0.68
A Ascendance 23.40 22.04 20.00 1.56 4.18**
S Sociability 22.14 21.56 20.48 0.56 1.83*
E Emot.Stab. 24.30 24.38 22.96 -0.11 1.75*
0 Objectivity 22.86 23.20 22.48 -0.38 0.44
F Friendliness 16.08 18.44 17.64 -2.46** -1.59
T Thoughtful 19.50 17.78 19.92 2.04* -0.47
P Pers.Rel. 23.78 23.90 22.46 -0.14 1.53
M Masculinity 21.98 22.13 21.65 -0.23 0.48
GPP-A Ascendancy 28.85 26.43 24.37 2.99** 6.11**
R Responsibility 28.32 29.60 30.02 -2.04* -2.53**
E Emot.Stab. 27.06 27.86 29.67 -0.95 -3.54**
S Sociability 22.44 21.51 20.46 1.02 2.47**
GPI-C Cautiousness 25.75 27.02 28.29 -1.89* -3.68**
0 Orig.Think. 31.67 30.77 31.35 1.18 0.40
P Pers.Rel. 25.66 27.19 27.40 -1.84* -2.20*
V Vigor 32.20 30.43 27.21 2.11* 5.74**
K-0 Outdoor 36.51 37.31 42.49 -0.29 -2.46**
1 Mechanical 43.16 44.30 43.90 -0.57 -0.40
2 Computation 29.62 30.34 29.96 -0.48 -0.25
3 Scientific 44.90 44.08 48.16 0.57 1.89*
4 Persuasive 52.44 44.94 42.94 2.65** 3.51**
5 Artistic 19.26 23.12 23.62 -2.49** -2.74**
6 Literary 22.90 23.42 2:3.08 -0.40 -0.14
7 Musical 13.40 12.52 12.58 0.80 0.72
8 Social Serv. 39.52 37.10 35.74 0.97 1.75*
9 Clerical 34.26 35.54 36.56 -0.61 -1.12
49
Table 2-Cont.
Variable
MRL Group Mean
t-
Test
I II III I-II I-III
SoV-T Theoretical 48.10 48.64 49.98 -0.41 -1.28
E Economic 49.58 48.60 45.90 0.59 2.22*
A Aesthetic 34.32 33.68 36.66 0.39 -1.45
S Social 32.32 30.98 30.98 1.12 1.04
P Political 44.08 43.52 42.88 0.43 0.97
R Religious 31.38 34.42 33.88 -1.49 -1.23
Bio-Data
Subject Age 41.46 41.56 41.48 -0.11 -0.02
-Age at first marriage 24.74 23.68 26.38 1.58 -1.95*
Recency last marriage 16.80 17.57 14.69 -0.55 1.48
Wife age at marriage 23.33 22.85 22.62 0.54 0.71
No. of children 2.88 2.86 2.36 0.07 1.62
Father's education 3.04 2.61 2.47 0.74 1.01
Mother's education 3.38 2.65 1.67 1.36 4.07**
No. of siblings 1.70 2.12 2.14 -1.19 -1.26
Brothers 0.96 1.24 1.10 -1.05 -0.56
Sisters 0.74 0.90 1.04 -0.87 -1.52
Brother's education 6.54 5.37 5.12 2.28* 2.94**
Sister's education 5.63 5.03 4.58 1.15 1.93*
Subject's education 7.04 6.76 6.76 1.29 1.39
Times major changed 0.12 0.14 0.22 -0.29 -1.11
No. jobs held 4.26 4.84 5.72 -1.42 -3.92**
Times moved back 0.39 0.51 0.63 -0.27 -0.49
Experience areas 2.12 1.46 1.24 4.73** 7.22**
Advanced degrees 0.66 0.48 0.42 1.32 1. 73*
Discharged or demoted 0.04 0.13 0.06 -0.55 -0.12
Times laid off 0.30 0.41 1.93 -0.57 -4.87**
Change to better job 2.00 1.90 0.48 0.36 5.79**
Publications 1.03 2.16 1.14 -1.52 0.31
Change for loc./health
Father's age when
0.09 0.24 0.65 -0.88 -2.89**
S born 29.36 31.03 28.32 -1.25 0.78
Types of remuneration
Mother's age when
1.00 0.42 0.06 0.98 1.75*
S born 26.51 27.44 26.51 -0.94 0.31
Wife's education 5.44 4.92 5.00 1.43 1.10
Age at first degree 22.56 23.16 25.08 -1.22 -4.00**
*P<.05, one-tail test, where 1 1.68
**p<.01, one-tail test, where 135 2.41
50
TABLE 3
SUMMARY OF SIGNIFICANT DIFFERENCES
BETWEEN MRL GROUPS
Variable
MRL I-II MRL I-III
.01 .05
•01
.05
MENTAL ABILITY TESTS:
Verbal Comprehension (EAS-1) X
Numerical Ability (EAS-2) X
Visual Speed & Accuracy (EAS-4) X
Numerical Reasoning (EAS-6) X
Verbal Reasoning (EAS-7) X X
Word Fluency (EAS-8) X X
Symbolic Reasoning (EAS-10) X
Total 2 7
PERSONALITY TESTS:
General Activity (GZ-G) X X
Ascendance (GZ-A) X
Sociability (GZ-S) X
Emotional Stability (GZ-F) X
Friendliness (GZ-F) X
Thoughtfulness (GZ-T) X
Ascendancy (GPP-A) X X
Responsibility (GPP-R) X X
Emotional Stability (GPP-E) X
Sociability (GPP-S) X
Cautiousness (GPI-C) X X
Personal Relations (GPI-P) X X
Vigor (GPI-V) X X
Outdoor (K-0) X
Scientific (K-3) X
Persuasive (K-4) X X
Artistic (K-5) X X
Social Service (K-8) X
Economic (SoV-E) X
Total 5 5 11 6
51
TABLE 3-Cont.
Variable
MRL I-II MRL 1-III
.01 .05 .01 .05
BIOGRAPHICAL FACTORS:
Age at first marriage X
Motherrs education X
Brotherrs education X X
Sister's education X
Number of jobs held X
Areas of Experience X X
Advanced degrees X
Times laid off X
Changed jobs to better self X
Changed jobs for location/health X
Types of remuneration X
Age at receipt of first degree X
Total 1 1 8 4
Grand Total 8 6 26 10
52
Significant differences between MRL I and MRL III subjects
at the .05 level or better totaled 36 in number. This
would certainly offer proof of the validity of Hi which
contends that significant differences in mental ability,
personality, and biographical factors do exist between
MRL groups.
The formulation of Hi also included some expecta
tion of the direction of correlation of test variables
with MRL groups. Table 4 indicates the predicted and
actual direction of correlation. Twenty-three variables
were expected to be positively correlated with MRL groups.
Of these, five had no correlation and two others were
slightly negatively correlated. All five variables pre
dicted to be negatively correlated with MRL groups were
negatively correlated. The remaining 13 test variables
for which no prediction was made (because it was felt no
positive or negative correlation would be found) had three
positively and six negatively correlated variables. It
should be pointed out that by positive (or negative) cor
relation, it was felt that test scores would decrease (or
increase) with each lower MRL group. No statistical
significance testing levels were involved in this part of
the investigation of Hi.
2. Discriminating Variables
In testing to see if a small number of the total
53
TABLE 4
COMPARISON OF PREDICTED AND ACTUAL DIRECTION
OF TEST VARIABLE CORRELATION WITH
MRL GROUP
Predicted Actual
Variable Direction Direction
Verbal Comprehension (EAS-1)
Numerical Ability (EAS-2)
Visual Speed & Accuracy (EAS-4)
Space Visualization (EAS-5)
Numerical Reasoning (EAS-6)
Verbal Reasoning (EAS-7)
Word Fluency (EAS-8)
Symbolic Reasoning (EAS-10)
General Activity (GZ-G)
Ascendance (GZ-A)
Sociability (GZ-S)
Emotional Stability (GZ-E)
Objectivity (GZ-O)
Friendliness (GZ-F)
Thoughtfulness (GZ-T)
Personal Relations (GZ-P)
Masculinity (GZ-M)
Ascendancy (GPP-A)
Vigor (GPP-V)
Computational (K-2)
Persuasive (K-4)
Economic (SoV-E)
Political (SoV-P)
Restraint (GZ-R)
Cautiousness (GPI-C)
Personal Relation (GPI-P)
Artistic (K-5)
Religious (SoV-R)
Responsibility (GPP-R)
Sociability (GPP-S)
Original Thinking (GPI-O)
Outdoor (K-0)
Mechanical (K-l)
Scientific (K-3)
Literary (K-6)
Musical (K-7)
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
0
0
0
0
o
0
0
0
+
“f
+
+
+
+
+
+
+
+
0
0
0
0
0
+
+
+
4-
+
+
0
0
0
54
TABLE 4-Cont.
Variable
Predicted
Direction
Actual
Direction
Social Service (K-8) 0 +
Clerical (K-9) 0
-
Theoretical (SoV-T) 0
-
Aesthetic (SoV-A) 0 0
Social (SoV-S) 0 +
+ = positive correlation with MRL Group
- = negative correlation with MRL Group
0 = no correlation with MRL Group
55
70 variables could discriminate between the three MRL
groups, the stepwise multiple discriminant analysis tech
nique was used. The subjects were divided evenly into two
groups (odd and even numbered) and data on the even sub
jects were run to develop the discriminant equations with
an F to enter at the .01 level of significance (F^6.0).
The results were as follows:
Variable F Variable No.
General Activity (GZ-G) 15.62
Word Fluency (EAS-8) 9.35
Time Changed Job to Better Self 7.66
V021
V002
V067
The set of equation for these three variables was:
MRL I = .49763V002 + 1.55388V021 + .18272V067 - 33.41678
MRL II - .39099V002 + 1.31091V021 + .11509V067 - 22.38101
MRL III = .42198V002 + 1.17955V021 + .53579V067 - 20.45390
Using these equations, the data for the even subjects was
run and the program placed each subject in the MRL group
having the highest value for the equation for the group.
Subsequently the odd subjects data was used to validate
the discriminant function thus derived. The resultant MRL
group classifications were as follows:
Actual
Group
Group
Classed
Into
Even Model
Odd
Validation
I II III I II III
I 19 4 3 15 13 5
•
II 5 15 1 7 10 7
III
1 6 21 3 2
13
56
The chi-square value for the model was 56.66 and for the
validation it was 18.18. With four degrees of freedom a
chi-square value of 18.46 or greater is significant at the
.001 level and 13.28 at the .01 level.
When the F to enter whs set at the .05 level of
significance (Fg? 3.15), six variables were included in the
discriminant set as follows:
Variable F
General Activity (GZ-G) 15.62
Word Fluency (EAS-8) 9.35
Times Changed Jobs to Better Self 7.66
Verbal Reasoning (EAS-7) 5.86
Number of Jobs Held 5.05
Number of Siblings 3.87
Variable No
V021
V002
V067
V005
V061
V054
A set of three equations with these six variables was
generated and using these equations the odd subjects were
used to validate the model developed from the even subjects
with results as follow^:
^\Actual
Group
Group
Classed
Into .
Even Model
Odd '
Validation
I II III I II III
I 22 3 0 17 12 2
II 3 20 3 6 11 8
III 0 2 22 2 2 15
The chi-square value for the model was 93.40 and for the
validation it was 30.55. The addition of variables beyond
57
six added little to the discriminating power of the sets
Q C
of equations until a large number was used. J Thus, it was
found that as few as three, and no more than six of the
total of 70 variables were needed to produce a discriminant
matrix of the three subject groups whose chi-square value
was significant of the .01 level. This evidenced the
validity of H2.
3. Relation of Psychometric
Scores to Age
The correlations between psychometric test scores
and age are presented in Table 5. Mental ability test
scores1 correlation with age was relatively similar for all
three groups except for Verbal Comprehension (EAS-1) and
Numerical Ability (EAS-2). As might be expected, Verbal
Comprehension had a positive correlation with age (.05
level) for MRL III. However, no significant age correla
tion was found for MRL I and MRL II. Numerical Ability
had a negative correlation with age for MRL I and MRL II
but no significant correlation for MRL III. These results
would reinforce the contention that testing of subjects
early in their careers would not diminish the discrimina
tion power of the mental ability test scores and would in
-^Obviously as you approach the use of all 70
variables, your predictive model will approach 100 per
cent accuracy.
58
TABLE 5
CORRELATION BETWEEN AGE AND TEST SCORES
Test
Correlation
With Age
Test
Correlation
With Age
MRL I MRL II MRL III MRL I MRL II MRL III
EAS-1** -.03 .16 .24 K-6 -.14 .05 .09
EAS-2** -.31 -.27 .16 K-7 .12 .13 .22
EAS-4** -.23 -.49 -.28 K-8** .00 .45 -.24
EAS-5 -.19 -.30 -.28 K-9 .01 -.04 .00
EAS-6** -.38 -.24 -.16 SoV-T .08 .02 .11
EAS-7*** -.17 -.26 .07 SoV-E** .18 -.09 .14
EAS-8*** -.04 .16 .06 SoV-A -.24 -.22 .10
EAS-10** .17 -.25 -.19 SoV-S .00 .28 .14
gz-g*** .19 -.11 -.09 SoV-P -.12 .05 -.14
GZ-R -.15 -.01 .08 SoV-R .09 .02 -.29
gz-a** .01 .02 -.18
GZ-S** -.03 .32 -.28
GZ-E** -.09 .02 -.19
GZ-0 -.17 -.09 -.03
GZ-F* -.21 -.03 .13
GZ-T* -.12 .08 .08
GZ-P .25 .07 18
GZ-M -.14 -.21 -.23
GPP-A*** -.25 .09 -.17
GPP-R*** -.05 -.11 .11
GPP-E** .05 -.03 -.32
GPP-S** -.13 .17 - .02
GPI-C*** .12 .04 .03
GPI-0 -.39 .06 -.01
GPI-P*** .07 .18 -.32
GPI-V*** .12 .09 -.07
K-O** -.23 -.09 .35
K-l .01 -.25 .13
K-2 -.11 -.19 -.09
K-3** .05 -.25 -.02
K-4***
.17 .17 -.17
K-5*** -.10 -.29 -.01
^Variable discriminates between MRL I and MRL II
at the .05 level or better.
**Variable discriminates between MRL I and MRL III
at the .05 level or better.
***Variable discriminates between MRL I and MRL II
and between MRL I and MRL III at .05 level or better.
59
I fact, probably aid in the discrimination.
1 The remainder of the test scores for significant
discriminating variables are similar for all three groups
except for GZ-S (Sociability), GPP-E (Emotional Stability),
K-0 (Outdoor), and K-8 (Social Service). Thus, only four
i
I of the 20 remaining variables that significantly discrimi-
j nate between the groups are not similar in their correla-
1 tion with age. The GZ-S scores are positively correlated
| with age for MRL II and negatively correlated for MRL III.
I The GPP-E scores for MRL III are negatively correlated
!
; with age and this would tend to increase discrimination
(
; between MRL I and MRL III subjects tested early in their
' careers.
The K-0 scores for MRL III were positively corre-
I
i lated with age and therefore older MRL III subjects were
less like MRL I. For MRL II subjects the K-8 test scores
; were positively correlated with age and for MRL III sub-
! jects K-8 scores were negatively correlated. This indi-
cates that older MRL II subjects are more like MRL I and
older MRL III subjects are less like MRL I in this test
measure. Thus, with only a few exceptions, which may be
j attributed to chance, we can say that the findings of
Grimsley and Jarrett were supported by the results of this
J study and that H3 is also supported.
I
i
I
I
i
60
Further support of earlier Grimsley and Jarrett
findings in this area was obtained by computation of the
significance of differences between correlation coeffi
cients for the test variables which significantly differen
tiated between the groups. Of the twelve test variables
which significantly differentiate between MRL Groups I and
II at the .05 level or greater, only one variable had an
age correlation coefficient which was significantly differ
ent at the .05 level. This variable was Ascendancy
(GPP-A).
None of the twelve variables which significantly
discriminated between MRL Groups II and III had age
correlation coefficients which were significantly different
at the .05 level. This would indicate that in general,
the use of tests in the employment situation as part of
the management selection process would not adversely affect
older MRL III subjects being considered for MRL II posi
tions or older MRL II subjects being considered for MRL I
positions. (The use of the word ’’ affect1’ here does not
imply causation).
61
4. MRL II Group's Similarities to MRL I
and MRL III Groups
The results of discriminant analysis using the odd
numbered subjects for a model and even numbered subjects
for validation with three variables were as follows:
Actual
Group
Group
Classed
Into
Odd Model Even Validation
I II III I II III
I 16 7 3 14 6 4
II 7 13 6 6 8 2
III 2 5 16 5 11 19
Six of the MRL II subjects were classified incorrectly as
MRL I and eleven were incorrectly classified as MRL III.
Only eight MRL II subjects were classified correctly,
whereas 14 MRL I and 19 MRL III were classified correctly
out of the 25 in each group. In the even model/odd vali
dation case shown above in section.2 of this chapter,
15 MRL I and 13 MRL III subjects were correctly classified.
In MRL II, ten were classified correctly, while 13 were
incorrectly classed as MRL I and two were classed as MRL
III. In each case fewer'MRL II subjects were classified
correctly than either of the other two groups. In the
first case MRL II subjects appeared to be more like MRL III
subjects and in the second case they appeared to be more
like MRL I subjects.
Further support of H4 is given in a comparison of
t-test scores. Of the 70 variables, 14 were significantly
different (.05 level or better) between MRL II and MRL I.
Significant differences between MRL II and MRL III totaled
25. Thus, the MRL II group did not differ significantly
from MRL I in 56 variables and did not differ from MRL III
in 45 variables. By comparison MRL I and MRL III were not
significantly different on only 24 variables.
5. Impact of Biographical Data on Discrimination
Between MRL Groups
To determine the biographical data's impact on the
discrimination between MRL groups, computer runs were made
using both test and biographical data and then test data
only. The results for a best three variable model are
shown in Table 6. These results indicate that use of bio
graphical data in conjunction with test data does not
significantly improve the ability to discriminate between
MRL groups. In view of the potential lower reliability of
biographical data gathered from subjects relative to test
scores obtained from subjects, it would seem reasonable to
use test scores only. The comparisons shown in Table 6
are a validation of H5.
63
TABLE 6
COMPARISON OF DISCRIMINANT ANALYSIS RESULTS
USING TEST AND BIOGRAPHICAL DATA WITH
TEST DATA ONLY
Data Set
Validation
Group Classification'
Matrix
Chi**
Square
Value
Test and Bio Data
(2 test, 1 bio
variable)
Odd
Subjects
I II III
I 15 13 5
II 7 10 7
III 3 2 13
18.18
Test and Bio Date
(2 test, 1 bio
variable
Even
Subj ects
I 14 6 4
II 6 8 2
III 5 11 19
18.95
Test Data Only
(3 test
variables)
Odd
Subj ects
I 16 12 5
II 7 9 9
III 2 4 11
13.81
Test Data Only
(3 test
variables)
Even
Subj ects
I 17 10 5
II 7 6 4
III 1 9 16
20.39
*Matrix is the same as those shown earlier in this
chapter. Rows are MRL groups classes into; columns are
MRL groups subjects are actually in.
**A chi square value of — 13.28 is significant at
the .01 level and a value 2 : 18.46 is significant at the
.001 level for four degrees of freedom.
64
6. Other Biographical Factors
Many of the biographical variables in this study
were not measured on interval scales, and therefore were
not suitable for analysis by customary parametric methods.
Thus, to test for significance of differences for these
non-parametric variables the chi-square test was applied.
A summary of the findings is presented in Table 7. For
those variables whose differences between groups obviously
were not significant from inspection, the test was not
applied.
65
TABLE 7
NON-INTERVAL SCALE BIOGRAPHICAL
DATA SUMMARY
Variable Response
MRL Group
Per Cent *
Chi-
Square
Value
1 II III
101 Position 1. Non-Supervis ory 0 14 76
applied for 2. Supervisor-Mgr. LOO 86 24 N/A
102 Area ap 1. Financial 2 6 6
plied for 2. Engineering 2 50 76 N/A
3. Marketing/sales 2 6 2
4. Legal 0 2 0
5. Manufacturing 2 26 14
6. General Admin. 90 10 2
7. General Non-Admin 2 0 0
105 Marital 1. Single 4 0 2
status 2. Married 86 90 90 N/A
3. Divorced/
separated 0 2 2
4. Widowed 0 0 0
5. Second Marriage 10 8 4
110 Listed 1. Housewife 76 70 40
occupation 2. Other 24 30 60 2.75
of wife
111 Wife's 1. No data or
employment None 88 84 78
2. Part-time or 1.82
Full-time 12 16 22
113 Resi 1. Owns home 84 84 64
dential 2. Rents 14 16 22 N/A
status 3. Lives with other 2 0 0
*The chi-square values were computed from the raw
frequencies.
66
Table 7-Cont.
Variable Response
MRL Group
Per Cent
Chi-
Square
Value
I II III
114 Subject
home as
child
1. Broken before 18
2. Unbroken
12
88
12
88
26
74 4.37
117 Father's
occupation
when S was
child
1. Executive, owner
or professional
2. All other
74.
26
44
56
32
68 •
21.60(3)
118 Mother
worked
dur ing
childhood
1. Yes
2. No
30
70
23
77
23
77 N/A
119 Mother's
occupation
when S was
child
1. Housewife
2. Other
58
42
64
36
62
38 N/A
120 Subjects
listed phy
sical limi
tations
1. None
2. Minor
3.. Major
58
34
8
52
' 42
6
46
44
10
1.90
121 Position
among
s iblings
1. Only or oldest
2. Middle
3. Youngest
54
24
22
46
34
20
56
24
20
N/A
127 Area
lived in dur
ing childhood
1. Farm/small town
2. Large town/city
18
82
20
80
22
78 N/A
128 Lived
with in
early life
1. Mother & father
2. Other
92
8
96
4
90
10 N/A
129 Military
service
highest rank
1. Enlisted
2. Non-Com.
3. Officer
3
33
64
22
44
34
23
50
27
18.15(5)
67
Table 7-Cont.
Variable Response
MRL Group
Per Cent
Chi-
Square
I
F 1
Value
131 Under 1. Science 26 24 i 24
graduate field 2. Engineering 74 76 76 N/A
133 Best 1. Highly related
liked sub to present job 36 64 84 10.55(2)
jects in col 2. Not related 64 36 16
lege
134 College 1. None 70 72 68
work activity 2. Part-time 22 20 18 N/A
3. Some full-time 8 4 6
4. Full-time 0 4 8
135 Extra 1. Leadership 40 26 4
curricular 2. Participant 56 64 70 23.84(6)
activities 3. None listed 4 10 26
136 College 1. None listed 50 58 78
academic 2. One or more 50 42 22 8.83(1)
honoraries
137 Profes 1. None listed 30 18 42
sional mem 2. One or more 70 82 58 N/A
berships
138 Club or 1. None listed 38 52 68
society mem 2. One or more 62 48 32 11.68(2)
berships
139 Club or 1. None listed 66 76 86
society offi 2. One or more 34 24 14 5.48
cer
140 Employ 1. Unemployed 14 36 28
ment at test 2. Employed 86 64 72 N/A
ing
141 Current/ 1. Non-supervisory 2 0 82
last position 2. Supervisor/man. 98 100 18 N/A
148 Avg. yrs. 1. Less than 3 26 40 54
per job 2. Three or more 74 60 46 8.17(1)
68
Table 7-Cont.
Variable Response
MRL Group
Per Cent
Chi
Square
Value
I II III
151 Job liked
best
1. Most respon
sible
2. Other
60
40
54
46
28
72 11.61(2)
153 Leisure
t ime--
1. Solitary
activity
2. Other
40
60
56
44
76
24 13.30(2)
154 Newspaper
read daily
1. Yes
2. No
88
12
86
14
86
14 . N/A .
155 News
magazine
read regu
larly
1. None
2. One or more
26
74
44
66
52
48 7.41(1)
156 Tech. &
Prof.
Journals read
1. None
2. One or more
48
52
34
66
52
48 N/A
15 7 Business
Publications
read
1. None
2. One or more
30
70
64
36
72
28 20.08(3)
159 Education
beyond initi
al degree
1. One year or less
2. More than one
year
46
54
62
38
76
24 9.50(2)
160 Field of
additional ed
1. Business
2. Other or none
44
56
20
80
8
92 18.42(3)
161 Advanced
degree ob
tained
1. Yes
2. No
66
34
46
54
38
62 10.87(2)
69
Table 7-Cont.
Variable Response
MRL Group
Per Cent
Chi-
Square
Value
r
II III
Additional 1. Second
degrees Bachelor 0 2 4
2. M.S. 34 28 26 N/A
3. MBA 24 6 2
4. Law 0 2 0
5. Ph.D. 8 10 10
Significant at .05 level with 2 df.
(2) Significant at .01 level with 2 df.
(3) Significant at .001 level with 2 df.
(4) Significant at .05 level with 4 df.
(5) S i'gnif icant at .01 level with 4 df.
(6) Significant at .001 level with 4 df.
70
CHAPTER V
DISCUSSION AND CONCLUSIONS
Prior to a discussion of the results of this re
search and some conclusions related to their practical
significance it seems important to examine the degree to
which those results may be generalized. Some caution is
warranted in considering the subjects studied as repre
sentative of the three MRL groups in general. However,
they may be representative of those engineers and scien
tists who are in those groups. The engineer and scientist
population from which they were selected was fair sized
(1,144) and the time span over which the selected 150 sub
jects were tested was a reasonable length of 15 years
(1957 to 1972). Additionally, the subjects used were from
109 different companies from all geographical areas of the
country and representing about a dozen different indus
tries. Finally, the subjects' early education and training
were in twelve of the most common areas of engineering and
scientific disciplines generally found in industry.
However, there is some doubt about the representativeness
of two of the subject groups. It is probable that due to
the age matching process used, the MRL II and especially
71
the MRL III subjects were on the average older than are
applicants at these levels in general.
1. Engineers and Scientists as
Managerial Resources'
The key occupational group in a modern industrial
society is management. Yet the flow of high quality
personnel into managerial functions is far below current
demand. Therefore, it is important for industrial
organizations (both private and public) to identify and
cultivate managerial potential among its young people.
Furthermore, since technology plays such an important role
in the continued success of these organizations, the iden
tification of managerial talent in their younger techni
cally trained and educated people is especially important.
Unfortunately, much of the behavioral scientist's
interest in scientific and engineering talent over the
years has been focused on the definition and measurement
•3 7
of traits such as creativity and analytical skill.
Also, the large bulk of research related to identification
of managerial talent did not necessarily include the
special and very important subgroup of those persons in
industry with high technology backgrounds. Thus, this
o/:
John P. Campbell, jet al. Managerial Behavior,
Performance, and Effectiveness, (New York: McGraw-Hill
Book Company, 1970, p. 1).
37Lawshe and Balma, Principles of Personnel
Testing, Chapter 14.
72
study was an attempt to begin to fill the gap of research
in that important area of behavioral science and manage
ment. This is not to say that all managers at some
future time will come from high technology backgrounds.
However, it seems reasonable to assume that an increas
ingly large proportion of managerial talent will come
from that source as long as the importance of science and
technology continues to increase in our society.
2. Profiles of MRL Groups
All 150 subjects had graduated with a major, and
started out their careers, in engineering or science.
Because of this, it would seem reasonable to expect that
they might be more similar than different in mental
ability, personality, and even biographical data than sub
jects randomly selected from the male college graduate
population in general. Thus, the statistically signifi-
can differences found between MRL groups in this study
indicate that personal factors related to managerial at
tainment may transcend those factors related to motivation
toward engineering and science education and careers.
Mental Ability
The results of this research support Ghiselli's
proposition that intellectual capability is directly
73
related to attainment of managerial responsibility.38 The
average raw score for MRL I was greater than the average
raw score for MRL II and III in all eight mental ability
tests. Two of these differences between MRL I and III
(Verbal Reasoning and Word Fluency) were significant at
the .01 level. Seven of the differences between MRL I and
III (all except Space Visualization) were significant at
the .01 level. While all of the average scores for MRL II
were higher than MRL III, none were statistically signifi
cant. These findings would tend to support a conclusion
that mental ability, even within the very intellectually
capable population of engineers and scientists, is a key
factor differentiating the highest achievers of mana
gerial attainment from the rest of the population.
Personality
Examination of scores from the personality tests
(self-descriptive inventories) indicates that the most
significant personality factor related to level of mana
gerial responsibility attained was General Activity
(GZ-G). This trait or personality factor is characterized
by energy, vitality, rapid pace of activity, production,
efficiency, etc. Very closly related and also a
O Q
E.E. Ghiselli, "Testing in Management Selection:
State of the Art," Personnel Psychology 16, (1963),
pp. 109-113.
74
significant discriminator between MRL groups was Vigor
(GPI-V). Two other scores which are similar to each other
were also positively related to level of managerial at
tainment. They were Ascendance (GZ-A) and Ascendancy
(GPP-A). Both indicate an individual's tendency to take
an active leader role in groups, to be independent, and to
be assertive in relationships with others. That the
characteristics of high drive and energy and ascendance
would be positively related to managerial attainment is
evident from common sense as well as from these research
results.
Two other characteristics which were related to
managerial attainment were Persuasive (K-4) and Economic
values (SoV-E). Again, common sense as well as research
results might lead to the same conclusion related to these
traits.
Along with these positively related test measured
traits, there were a number of personality scores which
were also significant, but negatively related to mana
gerial attainment. These were Friendliness (GZ-F),
Responsibility (GPP-R), Emotional Stability (GPP-E),
Cautiousness (GPI-C), Personal Relations (GPI-P), and
Artistic (K-5). The inverse relationship between these
characteristics and managerial attainment may not neces
sarily be seen from common sense without a close look.
The GZ measure of Friendliness at the extreme
75
indicates tolerance of hostile actions and acceptance of
domination. A very low score on this item indicates a
belligerence and readiness to fight, hostility and re
sentment, desire to dominate, and resistance to domina
tion. It is quite probable that either an extreme high
or low score would not be condusive to high levels of
managerial attainment. However, it does seem reasonable
that scores toward the low end of this scale would be
more desirable for high level managers, and the study re
sults do indicate that the average GZ-F score is signifi
cantly lower for each higher MRL group.
Individuals who are able to stick to any tasks
assigned, who are persevering, and who can always be
relied upon, will score high on the GPP measure of Respon
sibility. Low scores on this measure indicate an inability
to stick to tasks that are not interesting and a tendency
to be flighty or irresponsible. Again in this trait, an
extreme high or low score may not be desirable for a top
manager. Staying too long with a dull and uninteresting
task or on the other hand not being able to stay at all
would seem undesirable traits for those who have ascended
to high levels of management.
High scores on the GPP Emotional Stability scale
are usually made by individuals who are well-balanced,
stable, and relatively free from anxieties and nervous
tension. Low scores are associated with excessive
76
anxiety, hypersensitivity, nervousness, and low tolerance
for frustation. Obviously, extremely low scores would
not indicate a trait desirable for managers at any level.
However, although the average score for MRL I was signi
ficantly lower than the lower groups, it was in the 53
percentile range for Gordon's norm group of 123 second-
level male executive, while the MRL III score was in the
70 percentile r a n g e . 39 Thus, it seems that an average
amount of this trait is desirable, but that higher than
average levels seem to be associated with lower levels of
managerial attainment. It does seem reasonable to assume
that the more stable a person is, the less would be the
drive or motivation to change situations or levels of
management.
At the high end of the scale, the GP1 measure of
Cautiousness indicates individuals who do not like to
take risks and consider matters very carefully before
making decisions. At the low end are those who are im
pulsive, make snap decisions, enjoy taking chances, and
seek excitement. Thus, the test scores in this research
indicate that the subjects who had achieved high levels
of managerial responsibility were those more prone to
take risks, but not overly so disposed.
39Qordon, Manual: Gordon Personal Profile, p. 7.
77
High scores on the GPI measure of Personal Rela
tions are made by individuals who have great faith and
trust in people, and are tolerant, patient and under
standing. Scores on the lower end of the scale reflect
lack of confidence in people, and a tendency to be criti
cal of others. This means that higher level managers, on
the average, have less faith and trust in their fellow
man than do lower level managers and supervisors. How
ever, this characteristic is not extreme (about the 40
percentile range for the Gordon norm group of 123 second-
level executives)
The Kuder measure of preference for Artistic
vocations indicates preference for work in areas such as
the theater, art, and architecture. While all MRL group
scores were low in this measure, the MRL I group score
was significantly lower than the other two groups. It
does seem reasonable that individuals interested and
motivated to seek power and responsibility at high levels
of management might have less interest in the artistic
vocations than those whose characteristics are less suited
for top managerial positions.
These findings related to personality factors
obtained from self-descriptive inventories do indicate
that there are a number of measurable personality factors
^Ibid. , p . 6 .
j which differentiate the attainers of the highest levels of
j “ —
! management from the rest of the engineer and scientist
!
i population. This is an important finding because it indi-
i
cates that discriminating personality differences do exist
in individuals who achieve different levels of managerial
I
' attainment even though they come from a population which
1
is normally considered homogeneous.
t Biographical Factors
Examination of the biographical data for the three
I MRL groups indicates that, even though the data may not be
j
I as reliable as test scores obtained under employment con-
i ditions, a number of interesting differences were evident.
| Some of these differences in the biographical data are
factors occurring after the subjects had graduated and were
* related to career performance. Consequently these may not
i
be useful in selection of younger engineers and scientists
l
; with managerial potential. Items not related to career j
I
performance may be helpful in discrimination of younger
! engineers and scientists when test data is not available
I or as a supplement to test scores.
In the interval scale data obtained from the
j biographical data sheets significant items not related to
| career performance included mother's education, sibling's
j education, and subject's age when initial degree in
!
! engineering or science was obtained. The MRL I group's
!
j mothers were better educated and so were their brothers
j _ _ _ _ _ _ _ _ _ . _ _ _ _ _ _ _ _ ._ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 79
I
and sisters. The fathers also had more education than
the fathers of the lower level subjects, but not signifi
cantly so. On the average, the age at which the subject
obtained his first degree in engineering or science was
j inversely related with managerial attainment.
i
Career related interval-scale variables that dis
criminate significantly between groups included number of
; jobs held, areas of experience, times laid off, times
changed jobs to obtain a better position, times changed
1 jobs for health or location, and types of remuneration.
In general, the subjects at higher levels had held fewer
different jobs, had experience in more areas outside of
‘ engineering, had been laid off less often, had changed
their jobs more often to obtain a higher level or more
responsible position, and had changed jobs less often
I because of health or desire for new location,
i The non-interval scale biographical data also
■ yielded some significant and interesting results. The
t
; proportion of subjects' fathers who had been executives,
| owners of their own businesses, or professionals such as
!
I
medical doctors or lawyers increased with each higher
| level MRL group. The MRL I group had attained signifi-
j
| cantly higher undergraduate academic achievement as mea-
j sured by the number who had been selected for memberships
I in academic honorary societies. More of them belonged to
I
i
i
i
80
and were officers in clubs or professional societies than
in the other groups. Fewer of them spent their leisure
time in solitary activities.
In addition to their undergraduate academic
achievements, the MRL I subjects had successfully com
pleted more advanced degree programs and the most preva
lent area of their graduate work was business administra
tion. Also more MRL I subjects had held leadership posi
tions in college extracurricular activities than the other
groups. The proportion of best liked college subjects of
the MRL I group that were highly related to the jobs held
when they were tested was less than the proportion for the
lower MRL groups. More of the MRL I subjects liked their
most responsible job best, and of those subjects who had
been in the military, a significantly larger number had
been officers. In summary, the most successful managers
had successful fathers, had been leaders in school and the
military, had achieved high undergraduate academic honors
and obtained advanced degrees. They had obtained some of
their additional education in business and enjoyed jobs
most where they had most responsibility.
3. The Matched Group/Discriminant
Analysis MethocT
The primary purpose of this research was to ex
amine the validity of a method to determine differences
between engineers and scientists in various levels of
81
management. This method, a combination of matched groups
and discriminant analysis, held constant certain moderator
variables which are normally associated with test per
formance and managerial achievement. The matching process
controlled the moderator variables of age and undergradu
ate education. The problem of dealing with the elusive
and difficult to define criterion of managerial effective
ness was dealt with by substituting the criterion obtained
in the "managerial market place." Classification of sub
jects as a top, middle, or supervisor level manager was
based upon level of managerial responsibility attained
and maintained for a number of years prior to assessment.
Levels were defined on the basis of breath of organiza
tional responsibility rather than position title.
The stepwise multiple discriminant analysis pro
vided a means for identifying those variables which best
discriminated between the three groups and to assess the
relative value of biographical data to the process. The
efficiency of this method is that it provided a way to
determine the significant variables to be considered in
selection and allows limiting those to a small number of
test scores which may be accurately obtained in the
employment situation.
In the actual use of this method for early iden
tification of managerial talent, any organization may
82
test its successful managers and, using these results,
develop their own discriminant equations. From correla
tion analysis, control of or correction for age can be
included in the selection process. It is believed that
this method could be very effective in screening out those
who would not qualify. It may also provide data on
training or behavioral modification programs necessary to
assist those who would qualify except for one or two
areas. The method is effective because it uses as selec
tion criterion the traits of those individuals who have
proven themselves in the specific "market place" that will
utilize those selected.
4. Test Scores and Age
Perhaps one of the most important findings of this
research has to do with the relationship between test
scores and the amount of time spent in MRL II and MRL III
positions. In general, age is an excellent measure of time
spent in middle or lower level managerial positions for
MRL II and III subjects. Therefore, older MRL II and III
subjects will probably have had more experience in these
managerial positions. However, this research indicates
that this greater experience does not adversely affect test
scores of older subjects in these MRL groups as compared to
scores of the next higher group to which they may seek
entry.
The only discriminating test variable for which the
age correlation was significantly different between MRL I
and II was Ascendancy (GPP-A). In this case the correla
tion with age for MRL II was positive while it was negative
for MRL I. Thus, the older MRL II subjects scores were
more like MRL I than the younger MRL II subjects. There
were no discriminating variables for which the age correla
tion between MRL II and III was significantly different.
This strongly supports the findings of Grimsley and
Jarrett that "increased time spent in middle level manage
ment positions does not cause middle managers to develop
middle manager responses to test items." This was true for
both mental ability and personality tests.
5. Summary
This study has shown that the more successful
managers among engineers and scientists do have real mea
surable traits which differ from the less successful mana
gers. It also appears that, in general, these traits do
not vary significantly with age, but for those that do,
the variation can be corrected or adjusted for the process
of selection of younger managerial talent.
The most significant area for age adjustment
will be in the timed tests of mental ability. The per
sonality measures did not seem to vary much with age and
therefore will not require such adjustments.
84
The use of biographical data, while interesting and
hLfiJLpJLul in rounding out the information about a subject,
does not significantly aid in discrimination when the po
tentially more reliable psychometric test scores are avail
able. The usefulness of the matched group/discriminant
analysis method is such that, even in a homogeneous group
such as engineers and scientists, statistically significant
discrimination can be obtained. To further test this,
similar studies using subjects from other functional areas
(e.g. finance, marketing, and production) should be
carried out.
Ghiselli states that at the lowest levels of
management the potential of those individuals with a high
degree of management talent often go unrecognized. The
lower level management jobs are routine and do not provide
intellectual challenges. Consequently, they may be boring
and therefore poorly d o n e . ^ 2 The lower level jobs, then,
frequently do not allow superior managerial potential to
manifest itself, and indeed may actually inhibit such
manifestation. Therefore, the truly enlightened organi
zation must provide itself with the means for the early
identification of true managerial potential among its
young people, especially its technically talented young
^Edwin E. Ghiselli, Explorations in Managerial
Talent, (Pacific Palisades, Calif.: Goodyear Publishing
Company, Inc. 1971, pp. 124-125).
85
people. It is hoped that this study has provided meaning
ful imputs to that vital effort.
86
APPENDIX A
PSYCHOMETRIC TEST DESCRIPTIONS
EMPLOYEE APTITUDE SURVEY (EAS)
Verbal Comprehension (EAS-1)
TIME LIMIT: 5 minutes MAXIMUM SCORE:30
NATURE OF THE TEST
The Employee Aptitude Survey Verbal Comprehension
Test is a measure of the ability to use words in commu
nication, thinking, and planning. Performance on this
test is highly indicative of reading speed and ability to
understand written or spoken instructions. Verbal ability
is the most important single aspect of "general intelli
gence." Good verbal comprehension is essential for
executive and administrative personnel, and for account
ants, secretaries, stenographers, professional personnel,
and most high level office workers. People who work pri
marily with their hands and eyes (laborers, parts in
spectors, and mechanical workers) and routine clerical
workers need not have high verbal comprehension scores.
Numerical Ability (EAS-2)
TIME LIMITS MAXIMUM SCORE
PART 1:2 minutes PART I: 25
PART 11:4 minutes PART II: 25
PART 111:4 minutes PART III: 25
TOTAL: 10 minutes TOTAL: 75
NATURE OF THE TEST
The Employee Aptitude Survey Numerical Ability
Test measures the ability to work easily with numbers, to
do simple arithmetic fast and accurately. Executive,
supervisory, engineering, accounting, sales, and many
types of clerical positions require good ability in this
area. The test is set up in three parts which are sepa
rately timed. Part I measures facility in working with
integers, Part II measures facility with decimals, and
Part III measures facility with common fractions. Al
though scores may be obtained for each part separately,
total score is recommended to obtain maximum reliability
and validity for most purposes.
88
Visual Speed and Accuracy (EAS-4)
TIME LIMIT:5 minutes MAXIMUM SCORE: 150
NATURE OF THE TEST
The Employee Aptitude Survey Visual and Accuracy
Test is a measure of the ability to see small details
quickly and accurately, as in visual inspection and cleri
cal work. The more detailed the ’’ paper work” required on
a job, the more important it is that the worker be high
in this ability. Performance on this test is especially
important in the evaluation of personnel for positions as
bookkeepers, accountants, general office clerks, typists,
stenographers, and operators of most kinds of office
machines. Most sales, supervisory, and executive posi
tions require above-average performance on this test.
Space Visualization (EAS-5)
TIME LIMIT: 5 minutes MAXIMUM SCORE:50
NATURE OF THE TEST
The Employee Aptitude Survey Space Visualization
Test is a measure of the ability to visualize forms in
space and manipulate objects mentally. This ability is a
critical requirement for draftsmen, engineers, and person
nel in technical positions. Space visualization is a
strong component of "mechanical aptitude." The ability to
read and interpret blueprints is also dependent on space
visualization. Performance on this test is predictive of
performance over wide ranges of mechanical jobs, ranging
from fork-lift operator to aviation mechanic.
Numerical Reasoning (EAS-6)
TIME LIMIT: 5 minutes MAXIMUM SCORE:20
NATURE OF THE TEST
The Employee Aptitude Survey Numerical Reasoning
Test is a measure of the ability to analyze logical rela
tionships and discover principles underlying such rela
tionships. Essentially this is the process of inductive
reasoning--making valid generalizations from specific
instances. This ability is an important ingredient of
"general intelligence" and enters into many types of prob
lem-solving which may be verbal or symbolic as well as
numerical. The important feature of this ability is the
discovery of principles, which is distinct and separate
89
from the ability to apply principles. This type of abili
ty is particularly important in technical, supervisory,
and executive positions. Performance on this test is also
predictive of on-the-job trainability and is recommended
in evaluating applicants for training positions in
general.
Verbal Reasoning (EAS-7)
TIME LIMIT: 5 minutes MAXIMUM SCORE:30
NATURE OF THE TEST
The Employee Aptitude Survey Verbal Reasoning Test
is a measure of the ability to analyze verbally stated
facts and to make valid judgments on the basis of the
logical implications of such facts. An important feature
of this test is that it measures the ability to decide
whether or not the available facts provide sufficient in
formation to support a definite conclusion. This ability
to organize, evaluate, and utilize available information
is an important aspect of administrative and technical
decision-making as well as everyday judgments. This test
is particularly recommended for executive, administrative,
supervisory, scientific, accounting, and technical main
tenance personnel.
Word Fluency (EAS-8)
TIME LIMIT: 5 minutes
NATURE OF THE TEST
The Employee Aptitude Survey Word Fluency Test is
a measure of flexibility and ease in verbal communica
tions. In contrast to verbal comprehension, word fluency
involves speed and freedom in using words rather than
understanding verbal meanings. Facility in self-expression
depends to a large degree on word fluency. This test is
particularly recommended in the evaluation of personnel
for positions requiring extensive oral and written expres
sion, such as salesmen, journalists, field representatives,
technical writers, receptionists, personal secretaries,
and executives.
Symbolic Reasoning (EAS-10)
TIME LIMIT: 5 minutes MAXIMUM SCORE:30
NATURE OF THE TEST
90
The Employee Aptitude Survey Symbolic Reasoning
Test is designed primarily for evaluating high-level
personnel, particularly in technical and scientific job
categories. This test is a measure of the ability to
manipulate abstract symbols mentally and to make judgments
and decisions which are logically valid. The ability to
evaluate whether adequate information is available to
make definite decisions is an important aspect of per
formance on this test. Much of the thinking required of
electronics trouble-shooters, data programmers, account
ants, engineers, and scientific personnel requires the
high-level form of evaluative reasoning which this test
measures.
91
GUILFORD-ZIMMERMAN TEMPERMENT
SURVEY (GZ)
The following is an interpretation of the traits
measured and the number of items in the test related to
each quality considered part of that trait.
Number
of
Positive Qualities Negative Qualities Items
G--General Activity
Rapid pace of activities. .,vs
Energy; vitality........... vs
Keeping in motion.........vs
Production;efficiency.....vs
Liking for speed.......... vs
Hurrying...................vs
Quickness of action.......vs
Enthusiasm;liveliness......
R--Restraint
Slow and deliberate pace...6
Fatigability................6
Pausing for rest........... 4
Low production;ineffi
ciency...................4
Liking for slow pace.......3
Taking time.................2
Slowness of action......... 2
2
Serious-mindedness..........................................8
Happy-go-lucky;carefree. . . .5
Deliberate.................vs Impulsive................... 5
Excitement- loving.......... 5
Persistent effort............. 3
Self-Control......... 3
A--Ascendance
Self defense.............. vs
Leadership habits.........vs
Speaking with individuals.vs
Speaking in public........vs
Persuading others.......... .
Being conspicuous.........vs
Bluffing.....................
S--Sociability
Having many friends and
acquaintances........... vs
Submissiveness. . .......... 9
Habits of following........7
Hesitation to speaking.....5
Hesitation to speaking.....2
2
Avoiding conspicuousness ... 2
2
Few friends and acquaint
ances .....................9
92
Entering into conversa
tions ...................vs
Liking social activities. .vs
Seeking social contacts ... vs
Seeking limelight. .......vs
E--Emotional stability
Evenness of moods,........vs
interests,energy,etc.
Optimism;cheerfulness vs
Composure.......... vs
Feeling in good health....vs
0--Obj ec t ivity
Being "thickskinned"......vs
F--Friendliness
Toleration of hostile
action...................vs
Acceptance of domination..vs
Respect for others........vs
T--Thoughtfulness
Reflectiveness;medita-
tiveness..................
Observing of behavior
in others ............
Interested in thinking....vs
Philosophically inclined....
Observing of self......
Mental poise.............. vs
Refraining from conversa
tions ..................... 6
Disliking social acti
vities ....................5
Avoiding social contacts...5
Shyness..................... 3
Avoiding limelight......... 2
Fluctuation of moods,......7
interests,energy,etc.
Pessimism;gloominess.......7
Perseveration of ideas
and moods.................6
Daydreaming.................3
Excitability................2
Feeling in ill health......2
Feelings of guilt,
loneliness or worry......3
Hypersensitiveness........10
Egoism;self-centeredness...8
Suspiciousness;fancying
of hostility............. 6
Having ideas of reference..4
Getting into trouble.......2
Belligerence;readiness to
fight.....................9
Hostility,resentment.......7
Desire to dominate.........5
Resistance to domination...5
Contempt for others........2
........ 8
6
Interested in overt
activity..................5
.............................4
.............................4
Mental disconcertedness.... 3
93
P--Personal relations
Tolerance of people.......vs
Faith in social insti
tutions ..................vs
M--Masculinity
Interest in masculine.....vs
activities and vocations
Not easily disgusted......vs
Hardboiled.................vs
Resistant to fear.........vs
Inhibition of emotional
express ions............. vs
Little interest in clothes
and styles.............. vs
Hypercriticalness of......13
people;faultfinding
habits.
Criticalness of insti
tutions ..................
Suspiciousness of others...
Self pity................. .
Interest in feminine.....
activities and vocations
Easily disgusted..........
Sympathetic...............
Fearful...................
Romantic interests.......
Emotional Expressive
ness ...................... 3
Much interest in clothes
and styles................2
Dislike of vermin.......... 2
NOTE:
The titles of the categories should be suggestive
of the kind of adjustment or behavior to be expected in
those with high or low scores. A high score indicates the
"positive" qualities and a low score the "negative"
qualities. Extreme positive qualities do not always indi
cate the best adjustment, but extreme negative ones are
likely to indicate trouble.
94
0 0 V O C O f ' ' - m c o ro
GORDON PERSONAL INVENTORY (GPI)
Meaning of the Four Scale Scores
High and low scores on each of the Gordon Personal
Inventory Scales are interpreted as follows:
Cautiousness (C)
Individuals who are highly cautious, who consider
matters very carefully before making decisions, and do not
like to take chances or run risks, score high on this
Scale. Those who are impulsive, act on the spur of the
moment, make hurried or snap decisions, enjoy taking
chances, and seek excitement, score low on this Scale.
Original Thinking (0)
High scoring individuals like to work on difficult
problems, are intellectually curious, enjoy thought-
provoking questions and discussions, and like to think
about new ideas. Low scoring individuals dislike working
on difficult or complicated problems, do not care about
acquiring knowledge, and are not interested in though-
provoking questions or discussions.
Personal Relations (P)
High scores are made by those individuals who have
great faith and trust in people, and are tolerant, patient,
and understanding. Low scores reflect a lack of trust or
confidence in people, and a tendency to be critical of
others and to become annoyed or irritated by what others
Vigor IY2
High scores on this Scale characterize individuals
who are vigorous and energetic, who like to work and move
rapidly, and who are able to accomplish more than the
average person. Low scores are associated with low vi
tality or energy level, a preference for setting a slow
pace, and a tendency to tire easily and be below average
in terms of sheer output or productivity.
95.
GORDON PERSONAL PROFILE (GPP)
Meaning of the Four Scale Scores
High and low scores on each of the Gordon Personal
Profile Scales are interpreted as follows:
Ascendancy (A)
Those individuals who are verbally ascendant, who
adopt an active role in the group, who are self-assured
and assertive in relationships with others, and who tend
to make independent decisions, score high on this Scale.
Those who play a passive role in the group, who listen
rather than talk, who lack self-confidence, who let others
take the lead, and who tend to be overly dependent on
others for advice, normally make low scores.
Responsibility (R)
Individuals who are able to stick to any job as
signed them, who are persevering and determined, and who
can be relied on, score high on this Scale. Individuals
who are unable to stick to tasks that do not interest
them, and who tend to be flighty or irresponsible, usually
make low scores.
Emotional Stability (E)
High scores on this Scale are generally made by
individuals who are well-balanced, emotionally stable, and
relatively free from anxieties and nervous tension. Low
scores are associated with excessive anxiety, hypersensi
tivity, nervousness, and low frustration tolerance. Gen
erally, a very low score reflects poor emotional balance.
Sociability (S)
High scores are made by individuals who like to be
with and work with people, and who are gregarious and
sociable. Low scores reflect a lack of gregariousness, a
general restriction in social contacts, and, in the ex
treme, an actual avoidance of social relationships.
96
STUDY OF VALUES (SoV)
The Study of Values aims to measure the relative
prominence of six basic interests or motives in personali
ty; the theoretical,' economic, aesthetic, social, politi
cal, and religious. The classification is based directly
upon Eduard Spranger’s Types of Men, a brilliant work
which defends the view that the personalities of men are
best known through a study of their values or evaluative
attitudes.
The test consists of a number of questions, based
upon a variety of familiar situations to which two al
ternative answers in Part I and four alternative answers
in Part II are provided. In all there are 120 answers,
20 of which refer to each of the six values. The subject
records his preferences numerically by the side of each
alternative answer. His scores on each page are then
added and the totals transcribed onto the score sheet.
The page totals belonging to each of the six values are
then summed. After applying certain simple corrections
these six total scores are plotted on a profile, so that
the subject may see the significance of his standing on all
the values simultaneously.
Spranger1s Types
*
In selecting his six types, Spranger may be said
to hold a somewhat flattering view of human nature. He
does not allow for formless or valueless personalities,
nor for those who follow an expedient or hedonistic philo
sophy of life. The neglect of sheerly sensuous values is
a special weakness in his typology. His attempt to reduce
hedonistic choices partly to economic and partly to
aesthetic values-seems unconvincing. If the present scale
appears to the user to take a somewhat exalted view of the
organization of personality--neglecting both the "baser"
values and values that are not permitted to reach the
level of conscious choice--the limitation must be-re~gardeci~
as inherent in Spranger’s original formulation.
1. The Theoretical. The dominant interest of the
theoretical man is the discovery of truth. In the pursuit
of this goal he characteristically takes a ’’cognitive”
attitude, one that looks for identities and differences;
one that divests itself of judgments regarding the beauty
or utility of objects, and seeks only to observe and to
reason. Since the interests of the theoretical man are
97
empirical, critical, and rational, he is necessarily anu
intellectualist, frequently a scientist or philosopher.''
His chief aim in life is to order and systematize his
knowledge.
2. The Economic. The economic man is character
istically interested in what is useful. Based originally
upon the satisfaction of bodily needs (self-preservation),
the interest in utilities develops to embrace the practi
cal affairs of the business world--the production,
marketing, and consumption of goods, the elaboration of
credit, and the accumulation of tangible wealth. This
type is thoroughly "practical" and conforms well to the
prevailing stereotype of the average American businessman.
The economic attitude frequently comes into con
flict with o’ ther values. The economic man wants education
to be practical, and regards unapplied knowledge as waste.
Great feats of engineering and application result from the
demands economic men make upon science. The value of
utility likewise conflicts with the aesthetic value, ex
cept when art serves commercial ends. In his personal
life the economic man is likely to confuse luxury with
beauty. In his relations with people he is more likely to
be interested in surpassing them in wealth than in domi
nating them (political attitude) or in serving them (social
attitude). In some cases the economic man may be said to
make his religion the worship of Mammon. In other in
stances, however, he may have regard for the traditional
God, but inclines to consider Him as the giver of good
gifts, of wealth, prosperity, and other tangible blessings.
3. The Aesthetic. The aesthetic man sees his
highest value in form and harmony. Each single experience
is judged from the standpoint of grace, symmetry, or fit
ness. He regards life as a procession of events; each
single impression is enjoyed for its own sake. He need
not be a creative artist, nor need he be effete; he is
aesthetic if he but finds his chief interest in the artis
tic episodes of life.
* It must not be thought that a high degree of
talent or attainment is necessary to qualify a person for
classification in this, or in any, type. According to
Spranger a person can best be understood not by his
achievements but by his interests and intentions.
98
The aesthetic attitude is, in a sense, diametri
cally opposed to the theoretical; the former is concerned
with the diversity, and the latter with the identities of
experience. The aesthetic man either chooses, with Keats,
to consider truth as equivalent to beauty, or agrees with
Mencken, that, ” to make a thing charming is a million
times more important than to make it true.f f In the eco
nomic sphere the aesthete sees the process of manufactur
ing, advertising, and trade as a wholesale destruction of
the values most important to him. In social affairs he
may be said to be interested in persons but not in the
welfare of persons; he tends toward individualism and
self-sufficiency. Aesthetic people often like the beau
tiful insignia of pomp and power, but oppose political
activity when it makes for the repression of individuality.
In the field of religion they are likely to confuse beauty
with purer religious experience.
4. The Social. The highest value for this type
is love of people. In the Study of Values it is the
altruistic or philanthropic aspect of love that is mea
sured. The social man prizes other persons as ends, and
is therefore himself kind, sympathetic, and unselfish.
He is likely to find the theoretical, economic, and
aesthetic attitudes cold and inhuman. In contrast to the
political type, the social man regards love as itself the
only suitable form of human relationship. Spranger adds
that in its purest form the social interest is selfless
and tends to approach very closely to the religious atti
tude.
5. The Political. The political man is interested
primarily in power. His activities are not necessarily
within the narrow field of politics; but whatever his
vocation, he betrays himself as a Machtmensch. Leaders in
any field generally have high power value. Since competi
tion and struggle play a large part in all life, many
philosophers have seen power as the most universal and
most fundamental of motives. There are, however, certain
personalities in whom the desire for a direct expression
of this motive is uppermost, who wish above all else for
personal power, influence, and renown.
6. The Religious. The highest value of the re
ligious man may be called unity. He is mystical, and
seeks to comprehend the cosmos as a whole, to relate him
self to its embracing totality. Spranger defines the
religious man as one "whose mental structure is perma
nently directed to the creation of the highest and abso
lutely satisfying value experience.” Some men of this
99
type are "immanent mystics," that is, they find their
religious experience in the affirmation of life and in
active participation therein. A Faust with his zest and
enthusiasm sees something divine in every event. The
"transcendental mystic," on the other hand, seeks to unite
himself with a higher reality by withdrawing from life; he
is the ascetic, and, like the holy men of India, finds the
experience of unity through self-denial arid meditation.
In many individuals the negation and affirmation of life
alternate to yield the greatest satisfaction.
100
KUDER PREFERENCE RECORD (K)
The specific uses of the Kuder Preference Record-
Vocational for vocational guidance are:
1. To point out vocations with which the student
may not be familiar but which involve activities of the
type for which he has expressed preference. Such voca
tions deserve to be considered in the light of measures of
ability. In no case, however, are preference scores in
tended as a substitute for measures of ability.
2. To check on whether a person's choice of an
occupation is consistent with the type of thing he ordi
narily prefers to do. If the choice has not been made on
the basis of familiarity with the occupation in question,
the choice may be a poor one. Sometimes an adolescent
makes a choice because he admires a person in the occupa
tion chosen, or because the occupation is being chosen by
friends, or because it is one which involves much prestige
for adolescents. A check on such choices is desirable
before preparation for a vocation is so far advanced that
a choice cannot be easily changed.
The Kuder Preference Record-Vocational is also in
tended for use in employee counseling, particularly in
improving the placement of employees. In many instances
an employee's satisfaction and efficiency can be improved
materially by putting him in the kind of work he enjoys,
provided he also has the necessary ability.
Scores are obtained in ten general areas. They
are numbered as follows for identification purposes: (0)
outdoor, (1) mechancial, (2) computational, (3) scientific,
(4) persuasive, (5) artistic, (6) literary, (7) musical,
(8) social service, and (9) clerical.
The following are examples of professional and
managerial occupations indicated by high scores for each
preference area:
Outdoor (0)
Fish and Game Warden
Tree Surgeon
101
Mechanical (1)
Plant Manager j
Contractor :
I
j
Engineer \
Computational (2) |
Accountant/Auditor j
Mathematics Professor j
I
Statistician I
i
i
Scientific (3) j
i
Engineer |
i
Dentist
Physician/Surgeon
Persuasive (4)
Author/Editor j
Sales Engineer
Buyer/Store Department Head
Artistic (5) j
I
Actor j
Architect j
!
Art Gallery Curator j
I
Literary (6) i
Author/Editor
Lawyer j
College Professor j
I
!
!
I
Composer
Arranger
Social Service (8)
Clergyman
Social and Welfare Worker
Personal and Employment Manager
Clerical (9)
Bookkeeper and Cashier
General Office Clerk
Business Machine Operator
BIBLIOGRAPHY
BIBLIOGRAPHY
Books
Afifi, A. A. and S. P. Azen. Statistical Analysis, A
Computer Oriented Approach. New York: Academic
Press, Inc., 1972.
Bentz, V. J. "The Sears Experience in the Investigation,
Description, and Prediction of Executive Be
havior," In Wickert, R. F., and D. E. McFarland
(Eds.), Measuring Executive Effectiveness. New
York: Appleton-Century-Crofts, 1967.
Bryant, Edward C. Statistical Analysis, (2nd Edition).
New York: McGraw-Hi11 Book Company, 1966.
Campbell, John P., et al. Managerial Behavior, Perform
ance, and EfTectivenessT New York: McGraw-Hill
Book Co., 1970.
Cronback, Lee J. Essentials of Psychological Testing,
(2nd Edition). New York: Harper & Row, Publish-
ers, Inc., 1960.
________ , and Goldine C. Gleser. Psychological Tests and
Personnel Decisions, (2nd Edition). Urbana,
Illinois: University of Illinois Press, 1965.
Filley, Alan C. and Robert J. House. Managerial Process
and Organizational Behavior. Glenview, Illinois:
Scott, Foresman and Company, (Chapter 16), 1969.
Ghiselli, Edwin E. Explorations in Managerial Talent.
Pacific Palisades, California: Goodyear
Publishing Company, Inc., 1971.
The Validity of Occuaptional Aptitude Tests.
New York: John Wiley and Sons, Inc., 1966.
_________. Theory of Psychological Measurement. New York
McGraw-Hill Book Company, 1964.
________ , and Clarence W. Brown. Personnel and Industrial
Psychology. New York: McGraw-Hill Book Company,
Inc., 1955.
Guilford, J. P. and Benjamin Fruchter. Fundamental
Statistics in Psychology and Education, (5th
Edition). New York: McGraw-Hill Book Company,
1973.
Guion, Robert M. Personnel Testing. New York: McGraw-
Hill Book Company, 1965.
Gulliksen, Harold. Theory of Mental Tests. New York:
John Wiley and Sons, Inc., 1950.
Holmen, Milton G., and Richard.F. Docter. Educational
and Psychological Testing. New York"* Russell
Sage Foundation, 1972.
Kirkpatrick, James J. Five-year Follow-up Study of the
American Chamber of Commerce Standard Application
for Employment FornT! American Chamber of
Commerce, Washington, April, 1966.
Lawshe, Charles H., and Balma, Michael J. Principles of
Personnel Testing, (2nd Edition). New York:
McGraw-Hill Book Company, 1966.
Meyer, Herbert H. A Research Study of the Use of Tests
and the Interview for Evaluating"Technical
Personnel. New York: General Electric Co., 1954.
Piotrowski, Z. A., and Rock, M. R. The Perceptanalytic
Executive Scale. New York: Grune and Stratton,
T M T . -------------
Rulon, Phillip J. , et. al. Multivariate Statistics for
Personnel Classification. New York: John Wiley
& Sons, Inc., 1967.
Strong, Edward K., Jr. Vocational Interests of Men and
Women. Stanford” California^ Stanford University
Press, 1943.
. . |
________ . Vocational Interests 18 Years After College. j
Minneapolis: University of Minnesota Press, 1955.:
106
Periodicals
Albrook, Robert C. "How to Spot Executives Early,"
Fortune, (July 1968), pp. 106-110.
Bowman, Garda W. "What Helps or Harms Promotability?"
Harvard Business Review, (Jan.-Feb. 1964),
pp. 7-26.
Byham, William C. "Assessment Centers for Spotting Future
Managers," Harvard Business Review 48, No. 4,
(July-August 1970), pp. 150-167.
Detman, Art Jr. "What Makes a Top Executive?" Dun* s
Review, (April 1972), pp. 58-60.
(Dicken, C. F. and J. D. Black. "Predictive Validity of
Psychometric Evaluations of Supervisors," Journal
i of Applied Psychology 49, (1965), pp. 34-47.
Dunnette, Marvin, D. "The Minnesota Engineering Analogies
: Test," Journal of Applied Psychology 37, (1953),
pp. 170-175.
jGhiselli, Edwin E. "Testing in Management Selection:
State of the Art," Personnel Psychology 16,
: (1963), pp. 109-113.
! Grimsley, Glen, and Jarrett, Hilton F. "The Relation of
Past Managerial Achievement to Test Measures
j Obtained in the Employment Situation: Methodology
i and Results," Personnel Psychology 26, (Spring
| 1973), PP: 31-48.
iHase, E. F. "The Validity of Assessment Techniques Based
| on Systematically Varied Information," Personnel
| Psychology 15, (1962), pp. 195-205.
J Kirkpatrick, James J. "Validation of a Test Battery for
! the Selection and Placement of Engineers,"
i Personnel Psychology 9, (1956), pp. 211-227.
I Korman, Abraham K. "The Prediction of Managerial
Performance: A Review," Personnel Psychology 21,
(1968), pp. 295-322.
107
Labovitz, George H. "More on Subjective Executive
Appraisal: An Empirical Study," Academy of
Management Journal 15, No. 3, (September 1972),
pp. 289-302.
' Mahoney, Thomas A., et al. "Predicting Managerial
j Effectiveness," Personnel Psychology 13, (1960),
pp. 147-163.
Mayo, George Douglas and Alexander A. Longo. "A Note
Concerning the Matched Group Design,” Personnel
Psychology 21, (1968), pp. 241-244.
Randle, C. Wilson. "How to Identify Promotable
Executives," Harvard Business Review 34, No. 3,
j (1956), pp. 122-1'3'4":
Rosen, E. H. "The Executive Personality," Personnel 36,
; (1959), pp. 8-20.
i
i Rulon, Phillip J. "Problems of Regression," Harvard
i Educational Review 11, No. 2, (March l94l),
! pp. 213-223'.-------
! Slusher, Allen, James Van Dylse and Gerald Rose.
"Technical Competence of Group Leaders, Managerial
l Role, and Productivity in Engineering Design
Groups," Academy of Management Journal 15, No. 2,
(June 1972), pp. 197-204.
Thorndike, Robert L. "Regression Fallacies in the
Matched Groups Experiment," Psychometrica 7, No. 2
(June 1942), pp. 85-102.
1 Reports
I
: Jasper, William. A Validity Study of Selection Techniques
i for Entry-Level Scientists and Engineers. Re-
! search paper delivered before the Western
i Psychological Association Convention in Anaheim,
California (April 14, 1973).
i Laurent, Henry. Summary Report of the Early Identifica
tion of Management Potential Research Project in
i Standard Oil Company (New Jersey) and Affiliated
! Companies, SONJ, Social Science Research Division,
1961.
108
Uhlaner, J. E. Human Performance, Jobs, and Systems I
Psychology--The SystemsMeasurement Bed, Presi- j
dential address to Division o£ Military Psychology,^
American Psychological Association, Miami, Florida,'
September 6, 1970.

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