Most Recent Additions*
Concentrations of criteria pollutants in the contiguous U.S., 1979 – 2015: Role of model parsimony in integrated empirical geographic regression
Sun-Young Kim, Matthew Bechle, Steve Hankey, Elizabeth (Lianne) A. Sheppard, Adam A. Szpiro, and Julian D. Marshall
Technical Considerations in the Use of the E-value
Tyler J. VanderWeele, Peng Ding, and Maya Mathur
Analysis of Covariance (ANCOVA) in Randomized Trials: More Precision, Less Conditional Bias, and Valid Confidence Intervals, Without Model Assumptions
Bingkai Wang, Elizabeth Ogburn, and Michael Rosenblum
Robust Inference for the Stepped Wedge Design
James P. Hughes, Patrick J. Heagerty, Fan Xia, and Yuqi Ren
Studying the Optimal Scheduling for Controlling Prostate Cancer under Intermittent Androgen Suppression
Sunil K. Dhar, Hans R. Chaudhry, Bruce G. Bukiet, Zhiming Ji, Nan Gao, and Thomas W. Findley
Cross-sectional HIV Incidence Estimation Accounting for Heterogeneity Across Communities
Yuejia Xu, Oliver B. Laeyendecker, and Rui Wang
Incorporating Historical Models with Adaptive Bayesian Updates
Philip S. Boonstra and Ryan P. Barbaro
A SPLINE-ASSISTED SEMIPARAMETRIC APPROACH TO NONPARAMETRIC MEASUREMENT ERROR MODELS
Fei Jiang and Yanyuan Ma
ROBUST ESTIMATION OF THE AVERAGE TREATMENT EFFECT IN ALZHEIMER'S DISEASE CLINICAL TRIALS
Michael Rosenblum, Aidan McDermont, and Elizabeth Colantuoni
Default Priors for the Intercept Parameter in Logistic Regressions
Philip S. Boonstra, Ryan P. Barbaro, and Ananda Sen
PHASE II ADAPTIVE ENRICHMENT DESIGN TO DETERMINE THE POPULATION TO ENROLL IN PHASE III TRIALS, BY SELECTING THRESHOLDS FOR BASELINE DISEASE SEVERITY
Yu Du, Gary L. Rosner, and Michael Rosenblum
Tuning Parameter Selection in Cox Proportional Hazards Model with a Diverging Number of Parameters
Andy Ni and Jianwen Cai
Variance prior specification for a basket trial design using Bayesian hierarchical modeling
Kristen Cunanan, Alexia Iasonos, Ronglai Shen, and Mithat Gonen
Using Multilevel Outcomes to Construct and Select Biomarker Combinations for Single-level Prediction
Allison Meisner, Chirag R. Parikh, and Kathleen F. Kerr
COMPARISON OF ADAPTIVE RANDOMIZED TRIAL DESIGNS FOR TIME-TO-EVENT OUTCOMES THAT EXPAND VERSUS RESTRICT ENROLLMENT CRITERIA, TO TEST NON-INFERIORITY
Josh Betz, Jon Arni Steingrimsson, Tianchen Qian, and Michael Rosenblum
OPTIMIZED ADAPTIVE ENRICHMENT DESIGNS FOR MULTI-ARM TRIALS: LEARNING WHICH SUBPOPULATIONS BENEFIT FROM DIFFERENT TREATMENTS
Jon Arni Steingrimsson, Joshua Betz, Tiachen Qian, and Michael Rosenblum
Optimized Variable Selection Via Repeated Data Splitting
Marinela Capanu, Colin B. Begg, and Mithat Gonen
Nonparametric variable importance assessment using machine learning techniques
Brian D. Williamson, Peter B. Gilbert, Noah Simon, and Marco Carone
Developing Biomarker Combinations in Multicenter Studies via Direct Maximization and Penalization
Allison Meisner, Chirag R. Parikh, and Kathleen F. Kerr
Combining Biomarkers by Maximizing the True Positive Rate for a Fixed False Positive Rate
Allison Meisner, Marco Carone, Margaret Pepe, and Kathleen F. Kerr
*Updated as of 01/17/19.