Individual Patient-Level Data Meta-Analysis: A Comparison of Methods for the Diverse Populations Collaboration Data Set

• Other Authors: Dutton, Matthew Thomas (authoraut)
• Format: Others
• Language: English; English
• Published: Florida State University
• Subjects: Statistics
• Online Access: http://purl.flvc.org/fsu/fd/FSU_migr_etd-0620

DerSimonian and Laird define meta-analysis as "the statistical analysis of a collection of analytic results for the purpose of integrating their findings. One alternative to classical meta-analytic approaches in known as Individual Patient-Level Data, or IPD, meta-analysis. Rather than depending on summary statistics calculated for individual studies, IPD meta-analysis analyzes the complete data from all included studies. Two potential approaches to incorporating IPD data into the meta-analytic framework are investigated. A two-stage analysis is first conducted, in which individual models are fit for each study and summarized using classical meta-analysis procedures. Secondly, a one-stage approach that singularly models the data and summarizes the information across studies is investigated. Data from the Diverse Populations Collaboration data set are used to investigate the differences between these two methods in a specific example. The bootstrap procedure is used to determine if the two methods produce statistically different results in the DPC example. Finally, a simulation study is conducted to investigate the accuracy of each method in given scenarios. === A Dissertation submitted to the Department of Statistics in partial fulfillment of the requirements for the degree of Ph.D.. === Degree Awarded: Spring Semester, 2011. === Date of Defense: December 2, 2010. === Individual Patient-level Data, IPD meta-analysis, Meta-analysis === Includes bibliographical references. === Daniel McGee, Professor Directing Dissertation; Betsy Becker, University Representative; Xufeng Niu, Committee Member; Jinfeng Zhang, Committee Member.