Page 1 |
Save page Remove page | Previous | 1 of 304 | Next |
|
small (250x250 max)
medium (500x500 max)
large ( > 500x500)
Full Resolution
All (PDF)
|
This page
All
Subset |
EXPLORING ROBUST ALTERNATIVES TO PEARSON’S r THROUGH
SECONDARY ANALYSIS OF PUBLISHED BEHAVIORAL SCIENCE DATA
by
Veronica Mejia Stuart
_______________________________________________________________________
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PSYCHOLOGY)
December 2008
Copyright 2008 Veronica Mejia Stuart
Object Description
| Title | Exploring robust aternatives to Pearson's r through secondary analysis of published behavioral science data |
| Author | Stuart, Veronica Mejia |
| Author email | roni.stuart@gmail.com; vymejia@usc.edu |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Psychology |
| School | College of Letters, Arts and Sciences |
| Date defended/completed | 2008-06-16 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-12-13 |
| Advisor (committee chair) | Wilcox, Rand |
| Advisor (committee member) |
John, Richard McClure, William Read, Stephen |
| Abstract | Eleven data sets from five recently published articles in the field of psychology were re-analyzed to examine the extent to which reliance on Pearson's r to assess the relationship between two variables resulted in missed information. The robust techniques examined include three robust alternatives to r: the percentage bend correlation, the Winsorized correlation, and the skipped correlation; and two simple (one-predictor) regression techniques: the Theil-Sen and Coakley-Hettmansperger regression estimators. Several variables from each study were selected to replicate the correlational findings in the originating study. The relationships between these variables were examined through computation of these alternatives to Pearson's r using S-Plus and R statistical software. The properties of each computed statistic or confidence interval were then qualitatively compared and contrasted. Results indicate that the skipped correlation may be best suited to efficiently and accurately assess the relationship between two variables. Applied researchers in the behavioral sciences are challenged to recognize the advantages of these robust alternatives to Pearson's r and other traditional statistical methods. |
| Keyword | correlation; Pearson's r; robust statistics; secondary analysis; skipped correlation |
| 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-m1926 |
| Rights | Stuart, Veronica Mejia |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Stuart-2418 |
| Archival file | uscthesesreloadpub_Volume23/etd-Stuart-2418.pdf |
Description
| Title | Page 1 |
| Full text | EXPLORING ROBUST ALTERNATIVES TO PEARSON’S r THROUGH SECONDARY ANALYSIS OF PUBLISHED BEHAVIORAL SCIENCE DATA by Veronica Mejia Stuart _______________________________________________________________________ A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (PSYCHOLOGY) December 2008 Copyright 2008 Veronica Mejia Stuart |
Comments
Post a Comment for Page 1
