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Abstract:
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Meta-analysis is the gold standard statistical approach to combine the results of multiple studies and to examine sources of heterogeneity and potential biases. This course will review fixed-effect and random-effects models, including the newly-recommended approaches, that underlie the combination of study results in meta-analysis; the use of study-level predictors in meta-regression; novel limit meta-analysis models to adjust for small-study effects and related reporting biases; and the synthesis of individual participant data. Throughout the course, participants will apply each model by using the SAS/STAT software and produce high-quality graphs, with original macros developed by the instructors. The target audience includes biostatisticians, data analysts, and quantitative researchers from academia, the pharmaceutical industry, the FDA and other government institutions with a basic knowledge of study design and regression modeling.
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