Primary studies are using complex models more and more. Slopes from multiple regression analyses are reported in primary studies, but
few scholars have dealt with how to combine multiple regression slopes. One of the problems in combining multiple regression slopes is that
each study may use a different regression model. The purpose of this research is to propose a method for combining partial regression slopes
from studies with different regression models. The method combines comparable covariance matrices to obtain a synthetic partial slope. The
proposed method assumes the population is homogeneous, and that the different regression models are nested. Elements in the sample covariance
matrix are not independent of each other, so missing elements should be imputed using conditional expectations. The Bartlett decomposition is
used to decompose the sample covariance matrix into a parameter component and a sampling error component. The proposed method treats the
sample-size weighted average as a parameter matrix and applies Bartlett’s decomposition to the sample covariance matrices to get their
respective error matrices. Since missing elements in the error matrix are not correlated, missing elements can be estimated in the error
matrices and hence in the parameter matrices. Finally the partial slopes can be computed from the combined matrices. Simulation shows the
suggested method gives smaller standard errors than the listwise-deletion method and the pairwise-deletion method. An empirical examination
shows the suggested method can be applied to heterogeneous populations. / 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. / Fall Semester 2017. / November 17, 2017. / bartlett decomposition, cholesky decomposition, conditional covariance matrix, dependency in sample covariance
matrix, meta-analysis, multiple regression analysis / Includes bibliographical references. / Betsy Jane Becker, Professor Directing Dissertation; Fred Huffer, University Representative; Yanyun
Yang, Committee Member; Insu Paek, Committee Member.
Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_604975 |
Contributors | Jeon, Sanghyun (author), Becker, Betsy Jane, 1956- (professor directing dissertation), Huffer, Fred W. (Fred William) (university representative), Yang, Yanyun (committee member), Paek, Insu (committee member), Florida State University (degree granting institution), College of Education (degree granting college), Department of Educational Psychology and Learning Systems (degree granting departmentdgg) |
Publisher | Florida State University |
Source Sets | Florida State University |
Language | English, English |
Detected Language | English |
Type | Text, text, doctoral thesis |
Format | 1 online resource (116 pages), computer, application/pdf |
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