Biostatistics is the science of obtaining, analyzing and interpreting data in order to understand and improve human health. The mission of the Department of Biostatistics at the University of North Carolina at Chapel Hill is to forge advances in science that benefit human health through profound and paradigm-shifting innovations in biostatistical methodology and theory as well as the thoughtful implementation of biostatistical methods in practice.

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Papers from 2014

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sanon : An R Package for Stratified Analysis with Nonparametric Covariable Adjustment, Atsushi Kawaguchi and Gary G. Koch

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Latent Supervised Learning for Estimating Treatment Effect Heterogeneity, Susan Wei and Michael R. Kosorok

Papers from 2013

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Parameter Estimation in Cox Proportional Hazard Models with Missing Censoring Indicators, Naomi Brownstein, Eric Bair, Jianwen Cai, and Gary Slade

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Cross-Validation for Nonlinear Mixed Effects Models, Emily Colby and Eric Bair

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Feature Elimination in Empirical Risk Minimization and Support Vector Machines, Sayan Dasgupta, Yair Goldberg, and Michael R. Kosorok

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Latent Supervised Learning, Susan Wei and Michael R. Kosorok

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Latent Supervised Learning for Survival Data, Susan Wei and Michael R. Kosorok

Papers from 2012

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Identification of biologically relevant subtypes via preweighted sparse clustering, Sheila Gaynor and Eric Bair

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Reader Reaction: On Variance Estimation for the Fine-Gray Model, Chenxi Li, Robert J. Gray, and Jason P. Fine

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A Multistage Non‐inferiority Study Analysis Plan to Evaluate Successively More Stringent Criteria for a Clinical Trial with Rare Events, Siying Li, Gary G. Koch, and Todd A. Schwartz DrPH

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Change-Point Models to Estimate the Limit of Detection, Ryan C. May, Haitao Chu, Joseph G. Ibrahim, Michael G. Hudgens, Abigail C. Lees, and David M. Margolis

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A Comparison of Methods for Generating Correlated Binary Variates with Specified Marginal Means and Correlations, John S. Preisser Jr. and Bahjat F. Qaqish

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Research Methods for Clinical Trials in Personalized Medicine: A Systematic Review, Zheng Ren, Marie Davidian, Stephen L. George, Richard M. Goldberg, Fred A. Wright, Anastasios A. Tsiatis, and Michael R. Kosorok

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Developing Adaptive Personalized Therapy for Cystic Fibrosis using Reinforcement Learning, Yiyun Tang and Michael R. Kosorok

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Empirical Pathway Analysis, without Permutation, Yi-Hui Zhou, William T. Barry, and Fred A. Wright

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Simple and accurate trend tests using a permutation approximation, Yi-Hui Zhou and Fred A. Wright

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Reinforcement Learning Trees, Ruoqing Zhu, Donglin Zeng, and Michael R. Kosorok

Papers from 2011

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ORTH: R and SAS Software for Regression Models of Correlated Binary Data Based on Orthogonalized Residuals and Alternating Logistic Regressions, Kunthel By, Bahjat F. Qaqish, John S. Preisser, Jamie Perin, and Richard C. Zink

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Causal Inference for Vaccine Effects on Infectiousness, M. Elizabeth Halloran and Michael Hudgens

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Deletion Diagnostics for Alternating Logistic Regressions, John S. Preisser, Kunthel By, Jamie Perin, and Bahjat F. Qaqish

Papers from 2010

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The Interactive Decision Committee for Chaemical Toxicity Analysis, Chaeryon Kang, Hao Zhu, Fred A. Wright, Fei Zou, and Michael R. Kosorok

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Group Testing for Case Identification with Correlated Responses, Samuel D. Lendle, Michael Hudgens, and Bahjat F. Qaqish

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Randomization-Based Inference within Principal Strata, Tracy L. Nolen and Michael Hudgens

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Partial Proportional Odds Models for Longitudinal Ordinal Data, John S. Preisser, Ceib Phillips, Jamie Perin, and Todd A. Schwartz

Papers from 2009

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Inverse Regression Estimation for Censored Data, Nivedita V. Nadkarni, Yingqi Zhao, and Michael R. Kosorok

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Graphical Displays for Clarifying How Allocation Ratio Affects Total Sample Size for the Two Sample Logrank Test, Benjamin R. Saville, Yong S. Kim, and Gary G. Koch

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Variable Selection by Bayesian Adaptive Lasso and Iterative Adaptive Lasso, with Application for Genome-wide Multiple Loci Mapping, Wei Sun, Joseph G. Ibrahim, and Fei Zou

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Reinforcement Learning Design for Cancer Clinical Trials, Yufan Zhao, Michael R. Kosorok, and Donglin Zeng

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Reinforcement Learning Strategies for Clincal Trials in Non-small Cell Lung Cancer, Yufan Zhao, Michael R. Kosorok, Donglin Zeng, and Mark A. Socinski

Papers from 2008

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A Simulation Experiment to Investigate the Distributional Behavior of Extreme Cook's Distance for GEE to Models with Contaminated Binary Responses, Kunthel By, John Preisser, and Bahjat Qaqish

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Performance of One-Step Approximation Relative to Exact Cluster Cook's Distance for GEE, John Preisser, Kunthel By, and Bahjat Qaqish

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Testing Variance Components in Multilevel Linear Models using Approximate Bayes Factors, Benjamin R. Saville, Amy H. Herring, Jay S. Kaufman, and David A. Savitz

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Analyzing Correlated Longitudinal and Survival Data in Clinical Trials Using Multivariate Time-to-Event Methods, Benjamin R. Saville, Amy H. Herring, and Gary G. Koch

Papers from 2007

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Applications of Extensions of Bivariate Rank Sum Tests to the Bilateral Crossover Design to Compare Two Treatments Through Four Sequence Groups, Atsushi Kawaguchi, Gary G. Koch, and Ratna Ramaswamy

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Testing random effects in the linear mixed model using approximate Bayes factors, Benjamin R. Saville and Amy H. Herring

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On Asymptotically Optimal Tests Under Loss of Identifiability in Semiparametric Models, Rui Song, Michael R. Kosorok, and Jason P. Fine

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Regression Models for Identifying Noise Sources in Magnetic Resonance Images, Hongtu Zhu, Yimei Li, Joseph G. Ibrahim, Xiaoyan Shi, Hongyu An, Yasheng Chen, Weili Lin, Daniel B. Rowe, and Bradley G. Peterson