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06/28/2023
The Metropolis algorithm: A useful tool for epidemiologists
The Metropolis algorithm is a Markov chain Monte Carlo (MCMC) algorithm ...
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06/19/2023
Empirical sandwich variance estimator for iterated conditional expectation g-computation
Iterated conditional expectation (ICE) g-computation is an estimation ap...
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05/15/2023
A Causal Inference Framework for Leveraging External Controls in Hybrid Trials
We consider the challenges associated with causal inference in settings ...
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05/01/2023
Fusing Trial Data for Treatment Comparisons: Single versus Multi-Span Bridging
While randomized controlled trials (RCTs) are critical for establishing ...
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03/02/2023
Transportability without positivity: a synthesis of statistical and simulation modeling
When estimating an effect of an action with a randomized or observationa...
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07/11/2022
Positivity: Identifiability and Estimability
Positivity, the assumption that every unique combination of confounding ...
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06/09/2022
Bridged treatment comparisons: an illustrative application in HIV treatment
Comparisons of treatments or exposures are of central interest in epidem...
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03/21/2022
Delicatessen: M-Estimation in Python
M-estimation is a general statistical approach that simplifies and unifi...
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02/03/2022
Estimating Point Exposure Effects on Count Outcomes with Observational Data
Causal inference methods can be applied to estimate the effect of a poin...
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11/04/2021
Estimating SARS-CoV-2 Seroprevalence
During the COVID-19 pandemic, governments and public health authorities ...
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03/08/2021
Generalizing trial evidence to target populations in non-nested designs: Applications to AIDS clinical trials
Comparative effectiveness evidence from randomized trials may not be dir...
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12/17/2020
Tutorial: Introduction to computational causal inference using reproducible Stata, R and Python code
The purpose of many health studies is to estimate the effect of an expos...
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11/25/2020