Handbook of Matching and Weighting Adjustments for Causal Inference 1st Edition

Handbook of Matching and Weighting Adjustments for Causal Inference, 1st Edition by Elizabeth A. Stuart is an essential, contemporary guide for researchers, clinicians, and analysts working with observational data. Clear, authoritative, and practical, this handbook immediately connects you with proven strategies to estimate treatment effects when randomized trials aren’t possible.

You’ll find concise explanations of core methods—matching algorithms, propensity score techniques, weighting adjustments, balance diagnostics, and variance estimation—alongside guidance on choosing and implementing approaches in real-world studies. Stuart’s expert voice turns complex statistical ideas into actionable workflows, illustrated with examples relevant to epidemiology, public health, economics, education, and the social sciences.

Whether you’re a graduate student designing a thesis, a data scientist analyzing program impact, or a policy analyst assessing interventions across the United States, Europe, Asia, or beyond, this book equips you to produce more credible causal conclusions. Emphasis on reproducible practice and interpretation ensures you’ll not only run methods correctly but also communicate results convincingly to scientific and nontechnical audiences.

Compact yet comprehensive, the handbook balances theory and application so you can apply matching and weighting confidently in observational studies. If you want to strengthen causal claims, improve study design, and enhance analytical transparency, this book is a practical investment for your professional library.

Order your copy today and bring clarity and rigor to your causal inference work with one of the field’s leading authorities.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.