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