1 citations · 1 across the 2 of their papers we have counts for
4 papers
Comparing causal estimands from sequential nested versus single point target trials: A simulation study
Catherine Wiener, Chase D. Latour, Kathleen Hurwitz +4
Sequential nested trial (SNT) emulation is a powerful approach for maximizing precision and avoiding time-related biases. However, there exists little discussion about the implied…
Bridged treatment comparisons: an illustrative application in HIV treatment
Paul N Zivich, Stephen R Cole, Jessie K Edwards +3
Comparisons of treatments, interventions, or exposures are of central interest in epidemiology, but direct comparisons are not always possible due to practical or ethical reasons.…
Machine learning for causal inference: on the use of cross-fit estimators
Paul N Zivich, Alexander Breskin
Modern causal inference methods allow machine learning to be used to weaken parametric modeling assumptions. However, the use of machine learning may result in complications for in…
DAG With Omitted Objects Displayed (DAGWOOD): A framework for revealing causal assumptions in DAGs
Noah A Haber, Mollie E Wood, Sarah Wieten +1
Directed acyclic graphs (DAGs) are frequently used in epidemiology as a method to encode causal inference assumptions. We propose the DAGWOOD framework to bring many of those encod…