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G-Formula for Observational Studies with Partial Interference, with Application to Bed Net Use on Malaria
Assessing population-level effects of vaccines and other infectious dise...
02/01/2021 ∙ by Kayla W. Kilpatrick, et al. ∙
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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 ...
11/24/2020 ∙ by Sarah A. Reifeis, et al. ∙
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diproperm: An R Package for the DiProPerm Test
High-dimensional low sample size (HDLSS) data sets emerge frequently in ...
08/30/2020 ∙ by Andrew G. Allmon, et al. ∙
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Power and Sample Size for Marginal Structural Models
Marginal structural models fit via inverse probability of treatment weig...
03/12/2020 ∙ by Bonnie E. Shook-Sa, et al. ∙
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Balanced Policy Evaluation and Learning for Right Censored Data
Individualized treatment rules can lead to better health outcomes when p...
11/13/2019 ∙ by Owen E. Leete, et al. ∙
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Estimands and Inference in Cluster-Randomized Vaccine Trials
Cluster-randomized trials are often conducted to assess vaccine effects....
10/08/2019 ∙ by Kayla W. Kilpatrick, et al. ∙
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Inverse Probability Weighted Estimators of Vaccine Effects Accommodating Partial Interference and Censoring
Estimating population-level effects of a vaccine is challenging because ...
10/08/2019 ∙ by Sujatro Chakladar, et al. ∙
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Exact Power of the Rank-Sum Test for a Continuous Variable
Accurate power calculations are essential in small studies containing ex...
01/14/2019 ∙ by Katie R. Mollan, et al. ∙
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Post-randomization Biomarker Effect Modification in an HIV Vaccine Clinical Trial
While the HVTN 505 trial showed no overall efficacy of the tested vaccin...
11/09/2018 ∙ by Peter B. Gilbert, et al. ∙
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Doubly Robust Estimation in Observational Studies with Partial Interference
Interference occurs when the treatment (or exposure) of one individual a...
06/19/2018 ∙ by Lan Liu, et al. ∙
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Randomization inference with general interference and censoring
Interference occurs between individuals when the treatment (or exposure)...
03/06/2018 ∙ by Wen Wei Loh, et al. ∙
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Average treatment effects in the presence of unknown interference
We investigate large-sample properties of treatment effect estimators un...
11/17/2017 ∙ by Fredrik Sävje, et al. ∙
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Causal Inference from Observational Studies with Clustered Interference
Inferring causal effects from an observational study is challenging beca...
11/13/2017 ∙ by Brian G. Barkley, et al. ∙
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