20 citations · 21 across the 10 of their papers we have counts for
11 papers
Accelerating Proximal Gradient-type Algorithms using Damped Anderson Acceleration with Restarts and Nesterov Initialization
Nicholas C. Henderson, Ravi Varadhan
Despite their frequent slow convergence, proximal gradient schemes are widely used in large-scale optimization tasks due to their tremendous stability, scalability, and ease of com…
Quantifying uncertainty of individualized treatment effects in right-censored survival data: A comparison of Bayesian additive regression trees and causal survival forest
Daijiro Kabata, Nicholas C. Henderson, Ravi Varadhan
Estimation of individualized treatment effects (ITE), also known as conditional average treatment effects (CATE), is an active area of methodology development. However, much less a…
Parameter-Expanded ECME Algorithms for Logistic and Penalized Logistic Regression
Nicholas C. Henderson, Zhongzhe Ouyang
Parameter estimation in logistic regression is a well-studied problem with the Newton-Raphson method being one of the most prominent optimization techniques used in practice. A num…
Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Genomic Data
Rupam Bhattacharyya, Nicholas Henderson, Veerabhadran Baladandayuthapani
Rapid advancements in collection and dissemination of multi-platform molecular and genomics data has resulted in enormous opportunities to aggregate such data in order to understan…
Nonparametric Analysis of Delayed Treatment Effects using Single-Crossing Constraints
Nicholas C. Henderson, Kijoeng Nam, Dai Feng
Clinical trials involving novel immuno-oncology (IO) therapies frequently exhibit survival profiles which violate the proportional hazards assumption due to a delay in treatment ef…
Improved Small Domain Estimation via Compromise Regression Weights
Nicholas C. Henderson, Ravi Varadhan, Thomas A. Louis
Shrinkage estimates of small domain parameters typically utilize a combination of a noisy "direct" estimate that only uses data from a specific small domain and a more stable regre…
Bayesian Bivariate Subgroup Analysis for Risk-Benefit Evaluation
Nicholas C. Henderson, Ravi Varadhan
Subgroup analysis is a frequently used tool for evaluating heterogeneity of treatment effect and heterogeneity in treatment harm across observed baseline patient characteristics. W…
Damped Anderson acceleration with restarts and monotonicity control for accelerating EM and EM-like algorithms
Nicholas C. Henderson, Ravi Varadhan
The expectation-maximization (EM) algorithm is a well-known iterative method for computing maximum likelihood estimates from incomplete data. Despite its numerous advantages, a mai…
Individualized Treatment Effects with Censored Data via Fully Nonparametric Bayesian Accelerated Failure Time Models
Nicholas C. Henderson, Thomas A. Louis, Gary L. Rosner +1
Individuals often respond differently to identical treatments, and characterizing such variability in treatment response is an important aim in the practice of personalized medicin…
AR(1) Latent Class Models for Longitudinal Count Data
Nicholas C. Henderson, Paul J. Rathouz
In a variety of applications involving longitudinal or repeated-measurements data, it is desired to uncover natural groupings or clusters which exist among study subjects. Motivate…
Making the cut: improved ranking and selection for large-scale inference
Nicholas C. Henderson, Michael A. Newton
Identifying leading measurement units from a large collection is a common inference task in various domains of large-scale inference. Testing approaches, which measure evidence aga…