Mendelian Randomization: A Practical Guide to Causal Inference

Go beyond running MR code. Learn how to design, diagnose, interpret, and report a Mendelian randomization study rigorously.

Mendelian Randomization: A Practical Guide to Causal Inference is a research-focused guide for graduate students, epidemiologists, biostatisticians, genetic epidemiologists, and researchers working with causal inference.

Rather than treating Mendelian randomization as a collection of statistical commands, this book follows the complete research process—from defining the causal question and understanding instrumental-variable assumptions to conducting analyses, diagnosing potential violations, interpreting results, and preparing a manuscript.

The book covers causal assumptions and DAGs, GWAS data and instrument selection, Wald ratio, 2SLS and IVW, weak instruments, one-sample and two-sample MR, MR-Egger, weighted median and weighted mode, heterogeneity and horizontal pleiotropy, MR-PRESSO, Steiger directionality, bidirectional MR, multivariable MR, collider and selection bias, sample overlap and winner’s curse, MR-TRYX, MR-RAPS, CAUSE, LCV, Bayesian MR, drug-target and cis-MR, colocalization, and omics MR.

Practical sections include TwoSampleMR workflows, harmonization and quality control, sensitivity analyses, reproducible R workflows, publication-quality tables and figures, worked examples, STROBE-MR reporting, manuscript preparation, reviewer responses, and a pre-submission checklist.

The emphasis throughout is not simply on obtaining a statistically significant MR estimate, but on understanding what the estimate represents, which assumptions support it, what can invalidate it, and how strongly the evidence can be interpreted.

2026 Graduate Researcher Edition · 127 pages · PDF + EPUB

Author: Su Hyun Lee, PhD
PhD in Public Health, Yonsei University
Genetic Epidemiology & Causal Inference