A comprehensive range of user-written commands for meta-analysis is available in Stata and documented in detail in the recent book Meta-Analysis in Stata (Sterne, ed., 2009, [Stata Press]).The purpose of this session is to describe these commands, with a focus on recent developments and areas in which further work is needed. We will define systematic reviews and meta-analyses and will introduce the metan command, which is the main Stata meta-analysis command. We will distinguish between meta-analyses of randomized controlled trials and observational studies, and we will discuss the additional complexities inherent in systematic reviews of the latter. Meta-analyses are often complicated by heterogeneity, variation between the results of different studies beyond that expected due to sampling variation alone. Meta-regression, implemented in the metareg command, can be used to explore reasons for heterogeneity, although its utility in medical research is limited by the modest numbers of studies typically included in meta-analyses and the many possible reasons for heterogeneity. Heterogeneity is a striking feature of meta-analyses of diagnostic-test accuracy studies. We will describe how to use the midas and metandi commands to display and meta-analyse the results of such studies. Many meta-analysis problems involve combining estimates of more than one quantity: for example, treatment effects on different outcomes or contrasts among more than two groups. Such problems can be tackled using multivariate meta-analysis, implemented in the mvmeta command. We will describe how the model is fit, and when it may be superior to a set of univariate meta-analyses. Will will also illustrate its application in a variety of settings.
