12 citations · 29 across the 8 of their papers we have counts for
8 papers
Causal inference via propensity scores for case-control studies
Yan Liu, Anita Koushik, Philippe Boileau +5
Propensity score methods for causal inference are increasingly being used in cohort and experimental designs, but their development and uptake in outcome-dependent sampling schemes…
Identifying and Estimating Causal Direct Effects Under Unmeasured Confounding
Philippe Boileau, Nima S. Hejazi, Ivana Malenica +3
Causal mediation analysis provides techniques for defining and estimating effects that may be endowed with mechanistic interpretations. With many scientific investigations seeking…
Assumption-Lean Differential Variance Inference for Heterogeneous Treatment Effect Detection
Philippe A. Boileau, Hani Zaki, Gabriele Lileikyte +3
The conditional average treatment effect (CATE) is frequently estimated in clinical studies to refute a homogeneous treatment effect hypothesis. Under this regime, all patients mak…
Guidance on Individualized Treatment Rule Estimation in High Dimensions
Philippe Boileau, Ning Leng, Sandrine Dudoit
Individualized treatment rules, cornerstones of precision medicine, inform patient treatment decisions with the goal of optimizing patient outcomes. These rules are generally unkno…
A nonparametric framework for treatment effect modifier discovery in high dimensions
Philippe Boileau, Ning Leng, Nima S. Hejazi +2
Heterogeneous treatment effects are driven by treatment effect modifiers, pre-treatment covariates that modify the effect of a treatment on an outcome. Current approaches for uncov…
A Flexible Approach for Predictive Biomarker Discovery
Philippe Boileau, Nina Ting Qi, Mark J. van der Laan +2
An endeavor central to precision medicine is predictive biomarker discovery; they define patient subpopulations which stand to benefit most, or least, from a given treatment. The i…
Cross-Validated Loss-Based Covariance Matrix Estimator Selection in High Dimensions
Philippe Boileau, Nima S. Hejazi, Mark J. van der Laan +1
The covariance matrix plays a fundamental role in many modern exploratory and inferential statistical procedures, including dimensionality reduction, hypothesis testing, and regres…
A generalization of moderated statistics to data adaptive semiparametric estimation in high-dimensional biology
Nima S. Hejazi, Philippe Boileau, Mark J. van der Laan +1
The widespread availability of high-dimensional biological data has made the simultaneous screening of many biological characteristics a central problem in computational biology an…