54 citations · 145 across the 26 of their papers we have counts for
30 papers
Generalized Random Forests using Fixed-Point Trees
David Fleischer, David A. Stephens, Archer Y. Yang
We propose a computationally efficient alternative to generalized random forests (GRFs) for estimating heterogeneous effects in large dimensions. While GRFs rely on a gradient-base…
The impact of directly observed therapy on the efficacy of Tuberculosis treatment: A Bayesian multilevel approach
Widemberg S. Nobre, Alexandra M. Schmidt, Erica E. M. Moodie +1
We propose and discuss a Bayesian procedure to estimate the average treatment effect (ATE) for multilevel observations in the presence of confounding. We focus on situations where…
Bayesian inference for optimal dynamic treatment regimes in practice
Daniel Rodriguez Duque, Erica E. M. Moodie, David A. Stephens
In this work, we examine recently developed methods for Bayesian inference of optimal dynamic treatment regimes (DTRs). DTRs are a set of treatment decision rules aimed at tailorin…
A Bayesian Non-Stationary Heteroskedastic Time Series Model for Multivariate Critical Care Data
Zayd Omar, David A. Stephens, Alexandra M. Schmidt +1
We propose a multivariate GARCH model for non-stationary health time series by modifying the variance of the observations of the standard state space model. The proposed model prov…
A time-dependent Poisson-Gamma model for recruitment forecasting in multicenter studies
Armando Turchetta, Nicolas Savy, David A. Stephens +2
Forecasting recruitments is a key component of the monitoring phase of multicenter studies. One of the most popular techniques in this field is the Poisson-Gamma recruitment model,…
Causal inference: critical developments, past and future
Erica EM Moodie, David A Stephens
Causality is a subject of philosophical debate and a central scientific issue with a long history. In the statistical domain, the study of cause and effect based on the notion of `…