Multivariate meta-analysis refers to the statistical analyses of a collection of studies where at least some studies provide multiple effect-size estimates that may or may not represent multiple constructs. Multiple endpoint studies typically involve research designs where individuals in one treatment group and one control group produce measures on multiple variables. These types of studies will likely lead to statistically dependent effect sizes. The dependence that arises from multiple endpoint studies in the meta-analytic framework has not been thoroughly studied. The main purpose of this thesis was to investigate the impact of dependence from multiple endpoint studies utilizing homogeneity measures commonly found in current meta-analyses. This thesis is comprised of two sections: simulation and model estimation. Both sections replicated 3,000 meta-analyses for varying conditions. The simulation section varied study sample size, number of studies, between-outcomes correlation, and dependency structure. The model estimation section used generalized least squares estimation to analyze many of the same conditions. The standardized mean difference was the utilized effect-size estimator and Type I error rates of Q statistics were the primary unit of analysis. Results showed that increased dependence among effect sizes is associated with increased Type I error rates of Q statistics. More specifically, under very dependent conditions, Type I error rates were significantly greater than their nominal levels regardless of within-study sample size and number of studies, sometimes with more than a twofold inflation. The model estimation section demonstrated that using generalized least squares estimation to account for multiple endpoint dependency maintains Type I error rates within nominal levels and is preferable to incorrectly assuming independence. / A Thesis Submitted to the Department of Educational Psychology and Learning Systems
in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Summer Semester, 2011. / June 13, 2011. / Homogeneity, Meta-analysis, Multiple endpoints / Includes bibliographical references. / Betsy Becker, Professor Directing Thesis; Yanyun Yang, Committee Member; Daniel McGee, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_175944 |
| Contributors | Thompson, Christopher (authoraut), Becker, Betsy (professor directing thesis), Yang, Yanyun (committee member), McGee, Daniel (committee member), Department of Educational Psychology and Learning Systems (degree granting department), Florida State University (degree granting institution) |
| Publisher | Florida State University, Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource, computer, application/pdf |
| Rights | This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them. |
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