Causal-Inference

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.

A fun model to explain the surging popularity of Mendelian randomization

Ever wondered why Mendelian randomization is getting so popular?

Seeking a summer research intern (EXPIRED)

Seeking one student for a summer internship project on Mendelian randomization.

Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences

We reviewed the prevalence of different study designs in environmental and social sciences and introduced a novel model for with-study comparisons.