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72
linear correlation then a correlation ratio showing a curved line may illustrate a better
prediction of the relationship between the two variables.
Multiple regression statistics may be used to further refine the search for
predictor variables in the admission process. The multiple linear regression type of
multivariate correlational statistic is suggested for this phase of the study because it
is best for determining the correlation between a criterion variable and a set of
predictor variables when the correlation is expected to be linear. If the correlation is
not linear then the nonlinear regression type of multivariate correlational statistic will
be used.
Conclusion
The purpose of this research is to determine if data gathered in the admission
selection process of a community college based physician assistant program serve as
an indicator to predict the success or failure of students in the completion of the PA
program and passing the National Certification Examination. Existing data from
applicants’ file and data reported from the National Commission on the Certification
of Physician Assistants on student performance on the NCE was analyzed in this
study. Expert raters utilized holistic and analytic rubrics to rate letters of reference
and the personal statement to improve the reliability of data used from written
assessments. Correlations between predictor variables and prediction criterion was
performed to determine the correlation coefficients to indicate the significance of
relationship between the variables and the criterion. Bivariate statistics were used to
show the magnitude of the relationship between two variables and multiple
Object Description
| Title | A predictive valdity study: correlation of admission variables with program completion and student performance on the National Certification Examination in a physician assistant program |
| Author | Middleton, Delores E. |
| Author email | delores.middleton@rcc.edu; lolokinard@yahoo.com |
| Degree | Doctor of Education |
| Document type | Dissertation |
| Degree program | Education |
| School | Rossier School of Education |
| Date defended/completed | 2008-08-29 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-10-18 |
| Advisor (committee chair) | Jimenez y West, Ilda |
| Advisor (committee member) |
Cole, Darnell Hocevar, Dennis J. |
| Abstract | The purpose of this investigation was to examine the reliability and predictive validity of the of admission data in predicting student success in completing a community college-based physician assistant program and their performance on the National Certification Examination (NCE). The files of 170 graduates were reviewed and the following data was complied: 1) science grade point average (GPAsci), 2) cumulative grade point average (GPAcum), 3) reference letter ratings, 4) personal statement ratings, and 5) work experience -- each identified as a predictor measure in this study. The criterion measures identified in the study were 1) program completion, 2) performance on the NCE, and 3) skills. Findings demonstrated variations in the degree of relationship among predictor measures and criterion measures. The GPAsci demonstrated the greatest degree of correlation with student outcome in comparison with other predictor measures, which is consistent with previous research. Overall, the research demonstrated that there was practical significance or potentially significance correlations between the majority of the predictor measures. |
| Keyword | admission variable; criterion measures; national certification examination; criterion related evidence; reliability and predictive validy; prior academic achievement; letters of reference; personal statement; work experience |
| Coverage date | 1999/2005 |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m1678 |
| Contributing entity | University of Southern California |
| Rights | Middleton, Delores E. |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-Middleton-2420 |
| Archival file | uscthesesreloadpub_Volume32/etd-Middleton-2420.pdf |
Description
| Title | Page 80 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | 72 linear correlation then a correlation ratio showing a curved line may illustrate a better prediction of the relationship between the two variables. Multiple regression statistics may be used to further refine the search for predictor variables in the admission process. The multiple linear regression type of multivariate correlational statistic is suggested for this phase of the study because it is best for determining the correlation between a criterion variable and a set of predictor variables when the correlation is expected to be linear. If the correlation is not linear then the nonlinear regression type of multivariate correlational statistic will be used. Conclusion The purpose of this research is to determine if data gathered in the admission selection process of a community college based physician assistant program serve as an indicator to predict the success or failure of students in the completion of the PA program and passing the National Certification Examination. Existing data from applicants’ file and data reported from the National Commission on the Certification of Physician Assistants on student performance on the NCE was analyzed in this study. Expert raters utilized holistic and analytic rubrics to rate letters of reference and the personal statement to improve the reliability of data used from written assessments. Correlations between predictor variables and prediction criterion was performed to determine the correlation coefficients to indicate the significance of relationship between the variables and the criterion. Bivariate statistics were used to show the magnitude of the relationship between two variables and multiple |
