Individual Patient-level Data Meta-analysis: a Comparison of Methods for the Diverse Populations Collaboration Data Set

نویسندگان

  • Matthew Dutton
  • Daniel McGee
  • MATTHEW DUTTON
  • Betsy Becker
  • Xufeng Niu
  • Jinfeng Zhang
چکیده

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 metaanalysis 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.

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تاریخ انتشار 2010