27 citations · 52 across the 10 of their papers we have counts for
10 papers
A structural nested rate model for estimating the effects of time-varying exposure on recurrent event outcomes in the presence of death
Daniel Mork, Robert L. Strawderman, Michelle Audirac +2
Assessing the causal effect of time-varying exposures on recurrent event processes is challenging in the presence of a terminating event. Our objective is to estimate both the shor…
Causal inference for the expected number of recurrent events in the presence of a terminal event
Benjamin R. Baer, Trang Bui, Daniel Mork +2
While recurrent event analyses have been extensively studied, limited attention has been given to causal inference within the framework of recurrent event analysis. We develop a mu…
On the Role of Volterra Integral Equations in Self-Consistent, Product-Limit, Inverse Probability of Censoring Weighted, and Redistribution-to-the-Right Estimators for the Survival Function
Robert L. Strawderman, Benjamin R. Baer
This paper reconsiders several results of historical and current importance to nonparametric estimation of the survival distribution for failure in the presence of right-censored o…
Valid post-selection inference in Robust Q-learning
Jeremiah Jones, Ashkan Ertefaie, James R. McKay +2
Q-learning facilitates the development of an optimal adaptive treatment strategy through stagewise regression on a pre-specified set of tailoring variables and confounders. Semipar…
Causal Mediation Analysis: Selection with Asymptotically Valid Inference
Jeremiah Jones, Ashkan Ertefaie, Robert L. Strawderman
Researchers are often interested in learning not only the effect of treatments on outcomes, but also the pathways through which these effects operate. A mediator is a variable that…
Regression Trees and Ensembles for Cumulative Incidence Functions
Youngjoo Cho, Annette M. Molinaro, Chen Hu +1
The use of cumulative incidence functions for characterizing the risk of one type of event in the presence of others has become increasingly popular over the past decade. The probl…
Regression Trees for Cumulative Incidence Functions
Youngjoo Cho, Annette M. Molinaro, Chen Hu +1
The use of cumulative incidence functions for characterizing the risk of one type of event in the presence of others has become increasingly popular over the past decade. The probl…
Robust Q-learning
Ashkan Ertefaie, James R. McKay, David Oslin +1
Q-learning is a regression-based approach that is widely used to formalize the development of an optimal dynamic treatment strategy. Finite dimensional working models are typically…
Genomics models in radiotherapy: from mechanistic to machine learning
John Kang, James T. Coates, Robert L. Strawderman +2
Machine learning provides a broad framework for addressing high-dimensional prediction problems in classification and regression. While machine learning is often applied for imagin…
MM Algorithms for Minimizing Nonsmoothly Penalized Objective Functions
Elizabeth D. Schifano, Robert L. Strawderman, Martin T. Wells
In this paper, we propose a general class of algorithms for optimizing an extensive variety of nonsmoothly penalized objective functions that satisfy certain regularity conditions.…