A new approach to representing data from multiple regression designs is presented in this dissertation. The index, denoted as rsp, is the semi-partial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model, and represents a partial effect size in the correlation family. The derivations presented in this dissertation provide the partial effect size and its variance. Standard errors and confidence intervals can be computed for individual rsp values. Also, meta-analysis of the semi-partial correlations can proceed in a similar fashion to typical meta-analyses weighted analyses can be used to explore heterogeneity and to estimate central tendency and variation in the effects. A simulation study is presented to study the behavior of this index and its variance. / A Dissertation submitted to the Department of Educational Psychology and Learning
Systems in partial fulfillment of the requirements for the degree of Doctor of
Philosophy. / Degree Awarded: Spring Semester, 2009. / Date of Defense: April 7, 2009. / Research Synthesis, Meta-Analysis, Effect Size / Includes bibliographical references. / Betsy Jane Becker, Professor Directing Dissertation; Daniel McGee, Outside Committee Member; Akihito Kamata, Committee Member; Yanyun Yang, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_168254 |
| Contributors | Aloe, Ariel M. (authoraut), Becker, Betsy Jane (professor directing dissertation), McGee, Daniel (outside committee member), Kamata, Akihito (committee member), Yang, Yanyun (committee member), Department of Educational Psychology and Learning Systems (degree granting department), Florida State University (degree granting institution) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource, computer, application/pdf |
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