Session Chair: Chuck Huber, Stata
Meta-analysis is a statistical technique for combining the results from multiple similar studies. The talk will provide a brief introduction to meta-analysis and will demonstrate how to perform meta-analysis in Stata 16. The -meta- command offers full support for meta-analysis, from computing various effect sizes and producing basic meta-analytic summaries and forest plots to accounting for between-study heterogeneity and potential publication bias. Examples demonstrating how to conduct meta-analysis within Stata will be provided. These examples will focus on the interpretation of meta-analysis under various models, meta-regression, subgroup analysis, small-study effects and publication bias, and various types of forest, funnel, and other plots.