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The purpose of conducting a statistical analysis is to determine a summary estimate of effect. The effect measures could be rate difference, relative risk estimate (e.g. an odds’ ratio or relative risk) or a rate ratio. Selecting an effects model is important. Usually the choice is between fixed effects model, which indicates that the conclusions derived in the meta-analysis are valid for the studies included in the analysis, and random effects model, which assume that the studies included in the meta-analysis belong to a random sample of a universe of such studies. When the studies are found to be homogeneous, random and fixed effects models are indistinguishable. Finally, conduct a sensitivity analysis to test that the model you propose is a good model.