Causal-Inference

Multiple conditional randomization tests

Amusing counterfactual inference (by words)

My good friend Joshua Loftus and I spent some 30 minutes to crack (at least we think we did!) a counterfactual inference made in a speech in the House of Commons in London in 1850 by Lord Palmerston, who was the Secretary of State for Foreign Affairs at the time.

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?

Mendelian randomization

Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable exposures influence different outcomes. The principles of MR are based on Mendel’s laws of inheritance and …

Leverage Mendelian Randomization to Learn Meaningful Representations (LMR×2)

Multiple conditional randomization tests

Reliable Inference for Precision Medicine

Two central objectives of individualized treatment are precision and optimality. A third objective is robustness, and this talk aims to explore what could happen if we account for robustness in the decision process. The first case study is …

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 …

Statistical Modeling: Returning to its roots

Over this Easter weekend, I wrote the following commentary for the reprinting on Leo Breiman’s paper “Statistical Modeling: The Two Cultures” by Observational Studies. This is partly based on a talk I gave last year.