Design: The Elusive Principle of Statistics

Sensitivity analysis for observational studies: past, present, and future

Causal mediation analysis for time-varying heritable risk factors with Mendelian Randomization

A new Bayesian full-information method for life-course Mendelian randomization

Confounder selection via iterative graph expansion

Sensitivity analysis via stochastic programming

Confounder selection via iterative graph expansion

Confounder selection via iterative graph expansion

We propose a systematic way to select confounders

Almost exact Mendelian randomization

By combining causal graphs and randomization inference, a formal justification for Mendelian randomization is given in the context of with-family studies.

Sensitivity Analysis with the $R^2$-calculus

A new approach to sensitivity analysis in linear SEMs using stochastic optimization and the $R^2$-calculus

The randomization principle in causal inference: A modern look at some old ideas

Randomization is a fundamental principle in causal inference and was first proposed by R A Fisher about a century ago. Although randomization has now been universally adopted in the design of experiments, its role in the analysis of experiments and …