Biometrics & Biostatistics

Biography

Biography: Ken Williams

Abstract

This workshop will provide a brief overview of important features of meta-analysis. Topics will include: choosing between a fixed effect and a random effects model; accounting for correlations between statistics being compared; assessing the potential for bias; conducting subgroup analyses; doing meta-regression analysis; comparing the advantages and disadvantages of using published statistics versus individual-level data; doing Bayesian meta-analysis; choosing among available meta-analysis software; and applying parameters estimated by meta-analysis to support public health policy decisions. Examples will be provided from three published meta-analyses. One included all the 12 published reports from epidemiological studies that contained estimates of the relative risks of LDL-C, non-HDL-C, and apoB predicting fatal or nonfatal ischemic cardiovascular events. Another meta-analysis included 7 placebo-controlled statin trials in which LDL-C, non-HDL-C, and apoB values were available. The workshop leader was the lead analyst for these first two sample meta-analyses. The third sample meta-analysis was conducted by the Emerging Risk Factors Collaboration using individual-level epidemiological data from 3 studies which had published the relevant statistics and 23 which had not. All these sample meta-analyses were published in various journals. The workshop will wrap up with a discussion of how irreconcilable conclusions may be derived from different meta-analyses ostensibly pursuing the same objective.