23 citations · 41 across the 14 of their papers we have counts for
8 papers · 1 filter
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…
Assessing Vaccine Effectiveness in Observational Studies via Nested Trial Emulation
Justin B. DeMonte, Bonnie E. Shook-Sa, Michael G. Hudgens
Observational data are frequently used to evaluate real-world vaccine effectiveness (VE). For vaccines such as those developed against COVID-19, VE may vary over calendar time beca…
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…
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-…
Transportability without positivity: a synthesis of statistical and simulation modeling
Paul N Zivich, Jessie K Edwards, Eric T Lofgren +3
When estimating an effect of an action with a randomized or observational study, that study is often not a random sample of the desired target population. Instead, estimates from t…
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.…
Delicatessen: Automated Estimating Equations in Python
Paul N Zivich, Mark Klose, Stephen R Cole +2
Estimating equation theory provides a unified framework for statistical modeling and inference. Applying estimating equations has historically involved extensive matrix algebra and…
Exposure Effects on Count Outcomes with Observational Data, with Application to Incarcerated Women
Bonnie E. Shook-Sa, Michael G. Hudgens, Andrea K. Knittel +14
Causal inference methods can be applied to estimate the effect of a point exposure or treatment on an outcome of interest using data from observational studies. For example, in the…