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03/28/2023
Comparing Machine Learning Methods for Estimating Heterogeneous Treatment Effects by Combining Data from Multiple Randomized Controlled Trials
Individualized treatment decisions can improve health outcomes, but usin...
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03/09/2023
Sensitivity analysis for principal ignorability violation in estimating complier and noncomplier average causal effects
An important strategy for identifying principal causal effects, which ar...
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02/26/2023
Methods for Integrating Trials and Non-Experimental Data to Examine Treatment Effect Heterogeneity
Estimating treatment effects conditional on observed covariates can impr...
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01/17/2023
Multiple imputation for propensity score analysis with covariates missing at random: some clarity on within and across methods
In epidemiology and social sciences, propensity score methods are popula...
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02/11/2021
Clarifying causal mediation analysis: From simple to more robust strategies for estimation of marginal natural (in)direct effects
This paper aims to contribute to helping practitioners of causal mediati...
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11/25/2020
Sensitivity analyses for effect modifiers not observed in the target population when generalizing treatment effects from a randomized controlled trial: Assumptions, models, eff
Background: Randomized controlled trials are often used to inform policy...
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11/18/2020
Clarifying causal mediation analysis for the applied researcher: Effect identification via three assumptions and five potential outcomes
Causal mediation analysis is complicated with multiple effect definition...
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07/30/2019
Propensity score analysis with latent covariates: Measurement error bias correction using the covariate's posterior mean, aka the inclusive factor score
We address measurement error bias in propensity score (PS) analysis due ...
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04/17/2019