Meta-analysis provides a powerful tool for integrating findings from the research literature and building statistical models to explore trends and inconsistencies in the research base. Meta-analysis starts with a process for translating results from each study into an effect size that represents all findings in a common metric. Statistical models are then applied to estimate the mean, variance, and moderators of effect size. This article explores several key decision points in conducting a meta-analysis, including issues in obtaining a common metric, accounting for psychometric artifacts, and choosing an appropriate statistical model. It provides recommendations for choosing among alternate approaches and reporting results to ensure transparency.