Wow! eBook
The Data Analyst’s Guide to Cause and Effect: An Introduction to Causal Inference in Practice
Author(s): Theiss Bendixen (Author), Benjamin Grant Purzycki (Author)
- Publisher: SAGE Publications, Inc
- Publication Date: May 28, 2026
- Edition: First Edition
- Language: English
- Print length: 168 pages
- ISBN-10: B0G2M4XPFB
- ISBN-13: 9798348848712
Book Description
Built around the EEESI workflow―Estimand, Estimator, Estimate, Simulation-based Inference―this book provides a systematic approach to defining, estimating, and validating causal effects. Readers will learn to apply modern techniques such as g-methods, inverse probability weighting, poststratification, and multilevel modeling, while tackling challenges like confounding and missing data.
With hands-on examples in R, code snippets, and simulation exercises, this guide balances rigor with accessibility. Ideal for graduate courses and applied researchers, it equips readers to move beyond simple associations and make credible causal inferences that inform theory, policy, and practice.
Editorial Reviews
Review
The Data Analyst’s Guide to Cause and Effect offers an excellent, comprehensive, yet accessible introduction to causal inference. With a light-hearted approach, it opens up a new perspective for those accustomed to traditional statistical analysis, shedding light on crucial aspects of data interpretation. From selecting the right controls to estimating causal effects and even tackling advanced topics like missing data and the intricacies of multilevel modeling, this book is an invaluable guide for analysts seeking to move beyond mere correlation.
— Julia Rohrer
The Data Analyst′s Guide offers a strongly application-focused introduction to causal inference and is an effective tool for getting data analysts into the world of causal inference and immediately into a workable project. — Nicholas Huntington-Klein
This is a clear and readable book with broad coverage of many ideas and methods in causal inference. — Andrew Gelman
About the Author
volume, as well as more than 40 academic works, including tutorials, quantitative empirical papers, and technical commentaries. He consults on statistical modelling in both industry, academia, and non-profits, applying causal inference techniques across scientific disciplines. He currently works in the pharmaceutical sector.
Personal website: www.theissbendixen.com Benjamin Grant Purzycki is Associate Professor at Aarhus University. He is a cognitive and evolutionary cultural anthropologist and focuses on the causal role of various demographic and cultural factors on human cooperation. He has conducted fieldwork in the Tyva Republic (Russia) and managed large, cross-cultural projects. His most recent books include The Minds of Gods: New Horizons in the Naturalistic Study of Religion (Bloomsbury), Ethnographic Free-List Data (Sage), and Morality and the Gods (Cambridge University Press).
Personal website: www.bgpurzycki.wordpress.com