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Discusses the importance of the careful design of non-experimental studies, and the role of propensity scores in that design, with the main goal of providing practical guidance on the use of propensity scores in mental health research. Covers the primary ways of using propensity scores to adjust for confounders when estimating the effect of a particular “cause” or “intervention,” including weighting, sub classification, and matching. Examines issues such as how to specify and estimate the propensity score model, selecting covariates to include in the model, and diagnostics. Draws examples from school-based prevention research, drug abuse and dependence, and non-randomized treatment trials, among others. Primarily emphasizes non-experimental studies; however, also discusses applications to randomized trials.