A Weakly-Informative Group-Specific Prior Distribution for Meta-Analysis

• Other Authors: Thompson, Christopher (authoraut)
• Format: Others
• Language: English; English
• Published: Florida State University
• Subjects: Statistics; Educational psychology
• Online Access: http://purl.flvc.org/fsu/fd/FSU_2016SP_Thompson_fsu_0071E_13051

While Bayesian meta-analysis has flourished both in methodological and substantive work, group-specific Bayesian modeling remains scarce. Common practice for choosing prior distributions entails using typical non-informative priors. Currently, there is a push to use more informative prior distributions. In this dissertation I propose a group specific weakly informative prior distribution. The new prior distribution uses a frequentist estimate of between-studies heterogeneity as the noncentrality parameter in a folded noncentral t distribution. This new distribution is then modeled individually for groups based on some categorical factor. An extensive simulation study was performed to assess the performance of the new group-specific prior distribution to several non-informative prior distributions in a variety of meta-analytic scenarios. An application using data from a previously published meta-analysis on dynamic geometry software is also provided. === A Dissertation submitted to the Department Educational Psychology and Learning Systems in partial fulfillment of the requirements for the degree of Doctor of Philosophy. === Spring Semester 2016. === March 4, 2016. === Includes bibliographical references. === Betsy Jane Becker, Professor Directing Dissertation; Kathy Clark, University Representative; Russell Almond, Committee Member; Ariel M. Aloe, Committee Member; Yanyun Yang, Committee Member.