126 citations · 210 across the 6 of their papers we have counts for
6 papers
lmw: Linear Model Weights for Causal Inference
Ambarish Chattopadhyay, Noah Greifer, Jose R. Zubizarreta
The linear regression model is widely used in the biomedical and social sciences as well as in policy and business research to adjust for covariates and estimate the average effect…
A tutorial for using propensity score weighting for moderation analysis: an application to smoking disparities among sexual minority adults
Beth Ann Griffin, Megan S. Schuler, Matt Cefalu +5
Objective. To provide step-by-step guidance and STATA and R code for using propensity score (PS) weighting to estimate moderation effects. Research Design. Tutorial illustrating th…
Independence weights for causal inference with continuous treatments
Jared D. Huling, Noah Greifer, Guanhua Chen
Studying causal effects of continuous treatments is important for gaining a deeper understanding of many interventions, policies, or medications, yet researchers are often left wit…
Choosing the Causal Estimand for Propensity Score Analysis of Observational Studies
Noah Greifer, Elizabeth A. Stuart
Matching and weighting methods for observational studies involve the choice of an estimand, the causal effect with reference to a specific target population. Commonly used estimand…
Causal mediation analysis: From simple to more robust strategies for estimation of marginal natural (in)direct effects
Trang Quynh Nguyen, Elizabeth L. Ogburn, Ian Schmid +4
This paper aims to provide practitioners of causal mediation analysis with a better understanding of estimation options. We take as inputs two familiar strategies (weighting and mo…
MatchThem:: Matching and Weighting after Multiple Imputation
Farhad Pishgar, Noah Greifer, Clémence Leyrat +1
Balancing the distributions of the confounders across the exposure levels in an observational study through matching or weighting is an accepted method to control for confounding d…