Confounder selection, namely choosing a set of covariates to control for...
Negative control is a common technique in scientific investigations and
...
Causal inference necessarily relies upon untestable assumptions; hence, ...
Sensitivity analysis for the unconfoundedness assumption is a crucial
co...
Regression adjustment is broadly applied in randomized trials under the
...
Mendelian randomization (MR) is an observational design based on the ran...
Confounder selection is perhaps the most important step in the design of...
The meaning of randomization tests has become obscure in statistics educ...
We propose a general framework for (multiple) conditional randomization ...
This short note considers the problem of testing the null hypothesis tha...
In randomized clinical trials, adjustments for baseline covariates at bo...
We discuss some causal estimands used to study racial discrimination in
...
Mendelian Randomization (MR) is a popular method in epidemiology and gen...
The coronavirus disease 2019 (COVID-19) has quickly grown from a regiona...
It is common to compare individualized treatment rules based on the valu...
We present a comprehensive R software ivmodel for analyzing instrumental...
A persistent challenge in observational studies is that non-random
parti...
Mendelian randomization (MR) uses genetic variants as instrumental varia...
Mendelian randomization (MR) is an instrumental variable method of estim...
Mendelian randomization (MR) is a method of exploiting genetic variation...
To identify the estimand in missing data problems and observational stud...