Randomization Inference

Multiple conditional randomization tests

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.

Multiple conditional randomization tests

What is a randomization test?

The meaning of randomization tests has become obscure in statistics education and practice over the last century. This article makes a fresh attempt at rectifying this core concept of statistics. A new term---'quasi-randomization test'---is …

What is a randomization test?

Multiple conditional randomization tests

Multiple conditional randomization tests

We propose a general framework for (multiple) conditional randomization tests that incorporate several important ideas in the recent literature. We establish a general sufficient condition on the construction of multiple conditional randomization …

Cross-screening in observational studies that test many hypotheses

This paper proposes a new method called 'cross-screening' to increase the power of sensitivity analysis when multiple causal hypotheses need to be tested simultaneously.

On sensitivity value of pair-matched observational studies

A crucial quantity in Rosenbaum’s sensitivity analysis is the 'sensitivity value', the amount of unmeasured confounding needed to alter the qualitative conclusions of an observational study. This paper looks into the properties of 'sensitivity value' …

Permutation $p$-value approximation via generalized Stolarsky invariance

This paper uses a generalized Stolarsky's invariance principle to approximate the permutation $p$-value for two-sample linear test statistics. Along the way we discovered a simple probabilistic proof of Stolarsky's invariance principle.