activity
20202025
most citedTransportability without positivity: a synthesis of statistical and simulation modeling

23 citations · 31 across the 11 of their papers we have counts for

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8 papers · 1 filter

stat.ME2025

Confidence Regions for Multiple Outcomes, Effect Modifiers, and Other Multiple Comparisons

Paul N Zivich, Stephen R Cole, Noah Greifer +3

In epidemiology, some have argued that multiple comparison corrections are not necessary as there is rarely interest in the universal null hypothesis. From a parameter estimation p…

stat.ME2024

Double Robust Variance Estimation with Parametric Working Models

Bonnie E. Shook-Sa, Paul N. Zivich, Chanhwa Lee +5

Doubly robust estimators have gained popularity in the field of causal inference due to their ability to provide consistent point estimates when either an outcome or exposure model…

stat.ME2024

Finite sample performance of optimal treatment rule estimators with right-censored outcomes

Michael Jetsupphasuk, Michael G. Hudgens, Jessie K. Edwards +1

Patient care may be improved by recommending treatments based on patient characteristics when there is treatment effect heterogeneity. Recently, there has been a great deal of atte…

stat.ME2023★ 1 cited

Synthesis estimators for positivity violations with a continuous covariate

Paul N Zivich, Jessie K Edwards, Bonnie E Shook-Sa +3

Studies intended to estimate the effect of a treatment, like randomized trials, may not be sampled from the desired target population. To correct for this discrepancy, estimates ca…

stat.ME2023★ 3 cited

Empirical sandwich variance estimator for iterated conditional expectation g-computation

Paul N Zivich, Rachael K Ross, Bonnie E Shook-Sa +2

Iterated conditional expectation (ICE) g-computation is an estimation approach for addressing time-varying confounding for both longitudinal and time-to-event data. Unlike other g-…

stat.ME2023★ 1 cited

A Causal Inference Framework for Leveraging External Controls in Hybrid Trials

Michael Valancius, Herb Pang, Jiawen Zhu +3

We consider the challenges associated with causal inference in settings where data from a randomized trial is augmented with control data from an external source to improve efficie…