Causal-Inference

A unified analysis of regression adjustment in randomized experiments

Regression adjustment is broadly applied in randomized trials under the premise that it usually improves the precision of a treatment effect estimator. However, previous work has shown that this is not always true. To further understand this …

A crash course on causal inference

Multiple conditional randomization tests

Confounder selection: Objectives and approaches

We provide a unified review of various confounder selection criteria in the literature and the assumptions behind them.

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

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 …