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“Treatment Effects” books focus on how to determine and interpret the causal impact of an intervention—such as a medical therapy, public policy, educational program, A/B test, or marketing campaign—on outcomes of interest. This category spans the theory and practice of causal inference, covering study design and analysis strategies that separate cause from correlation, including randomized controlled trials, matching and propensity scores, difference-in-differences, instrumental variables, regression discontinuity, survival analysis, and meta-analysis of effect sizes. Titles explain core concepts like counterfactuals, selection bias, confounding, internal and external validity, and average versus heterogeneous effects, and they emphasize uncertainty and clear communication of results. Aimed at researchers, analysts, and practitioners across health, economics, social science, and business, these books range from methodological primers and software-guided workflows to applied case studies that inform evidence-based decision making.

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