
GFormula for Observational Studies with Partial Interference, with Application to Bed Net Use on Malaria
Assessing populationlevel effects of vaccines and other infectious dise...
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On variance of the treatment effect in the treated using inverse probability weighting
In the analysis of observational studies, inverse probability weighting ...
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diproperm: An R Package for the DiProPerm Test
Highdimensional low sample size (HDLSS) data sets emerge frequently in ...
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Power and Sample Size for Marginal Structural Models
Marginal structural models fit via inverse probability of treatment weig...
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Balanced Policy Evaluation and Learning for Right Censored Data
Individualized treatment rules can lead to better health outcomes when p...
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Estimands and Inference in ClusterRandomized Vaccine Trials
Clusterrandomized trials are often conducted to assess vaccine effects....
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Inverse Probability Weighted Estimators of Vaccine Effects Accommodating Partial Interference and Censoring
Estimating populationlevel effects of a vaccine is challenging because ...
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Exact Power of the RankSum Test for a Continuous Variable
Accurate power calculations are essential in small studies containing ex...
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Postrandomization Biomarker Effect Modification in an HIV Vaccine Clinical Trial
While the HVTN 505 trial showed no overall efficacy of the tested vaccin...
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Doubly Robust Estimation in Observational Studies with Partial Interference
Interference occurs when the treatment (or exposure) of one individual a...
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Randomization inference with general interference and censoring
Interference occurs between individuals when the treatment (or exposure)...
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Average treatment effects in the presence of unknown interference
We investigate largesample properties of treatment effect estimators un...
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Causal Inference from Observational Studies with Clustered Interference
Inferring causal effects from an observational study is challenging beca...
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Michael G. Hudgens
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