collaborators

5 papers

stat.ME2025

Computationally and statistically efficient estimation of time-smoothed counterfactual curves

Herbert P. Susmann, Nicholas T. Williams, Richard Liu +2

Longitudinal causal inference is concerned with defining, identifying, and estimating the effect of a time-varying intervention on a time-varying outcome that is indexed by a follo…

stat.ME2025

Time-smoothed inverse probability weighted estimation of effects of generalized time-varying treatment strategies on repeated outcomes truncated by death

Sean McGrath, Takuya Kawahara, Joshua Petimar +4

Researchers are often interested in estimating effects of generalized time-varying treatment strategies on the mean of an outcome at one or more selected follow-up times of interes…

stat.ME2025

Propensity score weighting across counterfactual worlds: longitudinal effects under positivity violations

Alec McClean, Iván Díaz

When examining a contrast between two interventions, longitudinal causal inference studies frequently encounter positivity violations when one or both regimes are impossible to obs…

stat.AP2025

Nonparametric estimation of an optimal treatment rule with fused randomized trials and missing effect modifiers

Nicholas Williams, Kara Rudolph, Iván Díaz

A fundamental principle of clinical medicine is that a treatment should only be administered to those patients who would benefit from it. Treatment strategies that assign treatment…

stat.ME2025

Asymptotically Efficient Data-adaptive Penalized Shrinkage Estimation with Application to Causal Inference

Herbert P. Susmann, Yiting Li, Mara A. McAdams-DeMarco +2

A rich literature exists on constructing non-parametric estimators with optimal asymptotic properties. In addition to asymptotic guarantees, it is often of interest to design estim…