Publications

Software
Psioda, Matthew, and Joseph G. Ibrahim. binDesign: Bayesian sample size for non-inferiority randomized trials with binary data (SAS).., 2016.
Psioda, Matthew, and Joseph G. Ibrahim. BetaBinPredProb: Compute predictive probabilities in Bayesian design for Phase IIA trials in a beta-binomial case (SAS).., 2016.
bcSeq: Fast Sequence Alignment for High-Throughput shRNA and CRISPR Screens (R)., 2017.
Ibrahim, Joseph G., and Matthew Psioda. BayesProp: Bayesian Clinical Trial Design for Regression Models Using Historical Data (SAS)., 2017.
Guo, Ruixin, Hongtu Zhu, Sy-Miin Chow, and Joseph G. Ibrahim. Bayesian Lasso for semiparametric structural equation models toolkit (C++).., 2011.
Eggleston, Barry S., Doug Wilson, Becky McNeil, Joseph G. Ibrahim, and Diane Catellier. BayesCTDesign: Two Arm Bayesian Clinical Trial Design with and Without Historical Control Data (R)., 2018.
Cao, Hongyuan, Donglin Zeng, Jason P. Fine, and Shannon T. Holloway. AsynchLong: Regression analysis of sparse asynchronous longitudinal data (R).. 2.0 ed., 2016.
Wang, WeiBo, Wei Wang, Wei Sun, James J. Crowley, and Jin P. Szatkiewicz. ASGENSENG: Detect Allele Specific CNV from Both WGS and WES Data (Python/Shell)., 2015.
Zhu, Anqi, Joseph G. Ibrahim, and Michael I. Love. apeglm: Approximate posterior estimation for GLM coefficients (R)., 2018.
X Jeng, Jessie, Zhongyin John Daye, Wenbin Lu, and Jung-Ying Tzeng. AFNC: Adaptive false negative control (R)., 2016.
Wang, Ting. AEBSD: Sample size of AEBSD and Comparison with BSD (R)., 2018.
Cornea, Emil, Hongtu Zhu, Peter Kim, and Joseph G. Ibrahim. ADNI_RMRSS: Regression Models on Riemannian Symmetric Spaces (MATLAB)., 2016.
Report
Zhu, Ruoqing, Donglin Zeng, and Michael R. Kosorok. Reinforcement learning trees In The University of North Carolina at Chapel Hill Department of Biostatistics Technical Report Series. UNC at Chapel Hill. Chapel Hill: The University of North Carolina, 2012.
Presentation
Davidian, Marie, Michael R. Kosorok, Eric B. Laber, and Anastasios A. Tsiatis. Workshop on Personalized Medicine and Dynamic Treatment Regimes., 2012.
Hung, H M. James. Utilities and challenges of adaptive designs in drug development., 2011.
Bretz, F. Tutorial: Introduction to Multiplicity in Clinical Trials., 2014.
Almirall, D. Tutorial: Getting SMART about Dynamic Treatment Regimes: A Conceptual Introduction., 2014.
Kang, Suhyun. Subgroup Detection and Sample Size Calculation with Proportional Hazards Regression for Survival Data., 2016.
Thall, PF. SMART Design, Conduct, and Analysis in Oncology., 2014.
Laber, Eric B.. Sizing a trial for estimation of an optimal treatment regime., 2014.
Levenson, M. Safety decision-making with multiple sources and different types of studies—recent examples from FDA Advisory Committees., 2011.
Davidian, Marie. A robust method for estimating optimal treatment regimes., 2011.
Bobashev, G. Prediction of the Best Treatment Assignment Using Random Forest with Regression in the Nodes., 2012.
Auman, Todd. Pharmacogenomic interrogation of colorectal cancer using next-generation whole exome sequencing., 2011.
Song, Rui. Penalized Q-Learning for Dynamic Treatment Regimes., 2012.
Heyse, Joseph F.. An Overview of Multiple Testing Procedures for Categorical Data., 2014.
Fine, Jason P.. An overview of competing risks data, with applications in clinical trials., 2011.
Rosenblum, M. Optimal, Two Stage, Adaptive Enrichment Designs for Randomized Trials, using Sparse Linear Programming., 2014.
Ivanova, Anastasia. Oncology Phase II trials with ordinal outcome., 2012.
Ibrahim, Joseph G.. Network Meta-analysis for Ordinal Outcomes: Applications in Comparing Crohn's Disease Treatments., 2016.
Xie, Jichun. Multiple Testing of General Dependence by Quantile-Based Contingency Tables with an Application in Identifying Gene Co-expression Network Change Associated with Cancer Survival., 2016.
Murphy, Susan A.. Micro-Randomized Trials & mHealth., 2014.
Zhao, Luping. Measures of Clinical Benefit in Immuno-Oncology Studies., 2016.
Shortreed, Susan M.. Leveraging Electronic Medical Records to Better Target Suicide Prevention., 2016.
Linn, Kristin A.. IQ-Learning., 2012.
Zhang, Yichi. Interpretable treatment regimes., 2014.
Wong, Kin Yau. Integration of Multiple High-dimensional Genomic Data Types for Survival Prediction., 2016.
Benjamini, Y. In Hochberg’s tradition: Selective Inference for Clinical Trials., 2014.
Sarkar, S. Improving Holm's procedure using pairwise dependencies., 2014.
Nair, Smita. Immune-based therapies., 2016.
Gou, J, and AC Tamhane. Hochberg Multiple Test Procedure Under Negative Dependence., 2014.
Almirall, D, and Susan A. Murphy. Getting SMART about developing individualized sequences of health interventions., 2012.
Chi, Eric. Getting High-throughput Arrays in Order with Convex Biclustering., 2016.
Tzeng, Jung-Ying. A gene-trait similarity regression method for gene-level pharmacogenetics analysis., 2011.
Li, Zhiguo. Fitting Cox models with doubly censored data using spline-based marginal likelihood., 2011.
Madar, V. Faster algorithm to control the Benjamini-Hochberg false discovery rate and its application for analysis of huge genomic data.., 2014.
Wang, L. Evaluation of Viable Dynamic Treatment Regimes in a Sequentially Randomized Trial of Advanced Prostate Cancer., 2014.
Zhao, Yingqi. Estimation of Optimal Dynamic Treatment Regimes., 2014.
Zeng, Donglin. Estimating treatment effects with treatment switching via semi-competing risks models: An application to a colorectal cancer study., 2011.
Zhao, Yingqi. Estimating Individualized Treatment Rules Using Outcome Weighted Learning., 2011.
Boland, Mary Regina. Electronic Health Records and Precision Medicine: Enabling Large-Scale Discoveries Using Phenome-Wide Approaches., 2016.
Madigan, D. Drug safety in spontaneous reports, observational databases, and clinical trials: Can we do better?., 2011.
Simon, R. Development of Predictive Biomarkers for Molecular Targeted Therapy., 2012.
Chen, Liddy M.. Design consideration for complex survival models., 2011.
Carpenter, William R.. Data needs for cancer comparative effectiveness research, and the Integrated Cancer Information and Surveillance System., 2012.
Rom, D. The Closure Principle Revisited., 2014.
Gatsonis, C. Clinical Evaluation of Diagnostic Tests and Biomarkers in CER., 2012.
Owzar, Kouros. Challenges in genome-wide association analysis of drug-induced toxicity data from clinical trials., 2012.
Sargent, Daniel J.. Biomarker-based clinical trials., 2012.
Korn, E. Biomarker-adaptive clinical trial designs., 2011.
Wang, Ting. Biomarker Stratified Design Enriched by Auxiliary Biomarker., 2016.
Wang, Xiaofei. Biased sampling and its applications in biomarker validation., 2011.
Chow, Shein-Chung. Benefits, Challenges and Obstacles of Adaptive Clinical Trial Designs., 2012.
Wahed, AS. Baseline Covariate Adjustment in SMART Studies via Artificial Randomization., 2014.
Murphy, Susan A.. Assessing Time-Varying Causal Interactions and Treatment Effects with Applications to Mobile Health., 2016.
Kidwell, KM. Addressing the Challenges and Reaping the Benefits of SMARTs., 2014.
Parmigiani, G. Adaptive randomized trial design for patients with recurrent glioblastom., 2011.
Laber, Eric B.. Adaptive inference after model selection., 2011.
Journal Article
Jusakul, Apinya, Ioana Cutcutache, Chern Han Yong, Jing Quan Lim, Mi Ni Huang, Nisha Padmanabhan, Vishwa Nellore, Sarinya Kongpetch, Alvin Wei Tian Ng, Ley Moy Ng et al. "Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma." Cancer Discov 7, no. 10 (2017): 1116-1135.
Bellach, Anna, Michael R. Kosorok, Ludger Rüschendorf, and Jason P. Fine. "Weighted NPMLE for the Subdistribution of a Competing Risk." J Am Stat Assoc 114, no. 525 (2019): 259-270.
Li, Jialiang, and Jason P. Fine. "Weighted Area Under the Receiver Operating Characteristic Curve and Its Application to Gene Selection." J R Stat Soc Ser C Appl Stat 59, no. 4 (2010): 673-692.
Li, Jialiang, and Jason P. Fine. "Weighted area under the receiver operating characteristic curve and its application to gene selection." Journal of the Royal Statistical Society: Series C (Applied Statistics) (2010).
Song, Rui, Feng Yi, and Hui Zou. "On Varying-coefficient Independence Screening for High-dimensional Varying-coefficient Models." Stat Sin 24, no. 4 (2014): 1735-1752.
Zhou, Jie, Jiajia Zhang, Alexander C. Mclain, Wenbin Lu, Xuemei Sui, and James W. Hardin. "A varying-coefficient generalized odds rate model with time-varying exposure: An application to fitness and cardiovascular disease mortality." Biometrics 75, no. 3 (2019): 853-863.
Yuan, Ying, Hongtu Zhu, Martin Styner, John H. Gilmore, and J S. Marron. "VARYING COEFFICIENT MODEL FOR MODELING DIFFUSION TENSORS ALONG WHITE MATTER TRACTS." Ann Appl Stat 7, no. 1 (2013): 102-125.
Zou, Baiming, Fei Zou, Jonathan J. Shuster, Patrick J. Tighe, Gary G. Koch, and Haibo Zhou. "On variance estimate for covariate adjustment by propensity score analysis." Stat Med 35, no. 20 (2016): 3537-48.
He, Qianchuan, and Dan-Yu Lin. "A variable selection method for genome-wide association studies." Bioinformatics 27, no. 1 (2011): 1-8.
Stefanski, L A., Yichao Wu, and Kyle White. "Variable Selection in Nonparametric Classification via Measurement Error Model Selection Likelihoods." J Am Stat Assoc 109, no. 506 (2014): 574-589.
White, Kyle R., Leonard A. Stefanski, and Yichao Wu. "Variable Selection in Kernel Regression Using Measurement Error Selection Likelihoods." J Am Stat Assoc 112, no. 520 (2017): 1587-1597.
Zhang, Xiang, Yichao Wu, Lan Wang, and Runze Li. "Variable Selection for Support Vector Machines in Moderately High Dimensions." J R Stat Soc Series B Stat Methodol 78, no. 1 (2016): 53-76.
Lu, Wenbin, Hao Helen Zhang, and Donglin Zeng. "Variable selection for optimal treatment decision." Stat Methods Med Res 22, no. 5 (2013): 493-504.
Lin, Chen-Yen, Howard Bondell, Hao Helen Zhang, and Hui Zou. "Variable Selection for Nonparametric Quantile Regression via Smoothing Spline AN OVA." Stat 2, no. 1 (2013): 255-268.
Yuan, Shuai, Hao Helen Zhang, and Marie Davidian. "Variable selection for covariate-adjusted semiparametric inference in randomized clinical trials." Stat Med 31, no. 29 (2012): 3789-804.
Wang, Xiaofei, Lin Gu, Ying Zhang, Daniel J. Sargent, William Richards, Apar Kishor Ganti, Jeffery Crawford, Harvey Jay Cohen, Thomas Stinchcombe, Everett Vokes et al. "Validation of survival prognostic models for non-small-cell lung cancer in stage- and age-specific groups." Lung Cancer 90, no. 2 (2015): 281-7.
Wang, Xiaofei, Xiaoyi Wang, Lydia Hodgson, Stephen L. George, Daniel J. Sargent, Nate R. Foster, Apar Kishor Ganti, Thomas E. Stinchcombe, Jeffrey Crawford, Robert Kratzke et al. "Validation of Progression-Free Survival as a Surrogate Endpoint for Overall Survival in Malignant Mesothelioma: Analysis of Cancer and Leukemia Group B and North Central Cancer Treatment Group (Alliance) Trials." Oncologist 22, no. 2 (2017): 189-198.
Liu, Yufeng, Yichao Wu, and Qinying He. "Utility-based Weighted Multicategory Robust Support Vector Machines." Stat Interface 3, no. 4 (2010): 465-476.
Shook-Sa, Bonnie E., Ding-Geng Chen, and Haibo Zhou. "Using Structural Equation Modeling to Assess the Links between Tobacco Smoke Exposure, Volatile Organic Compounds, and Respiratory Function for Adolescents Aged 6 to 18 in the United States." Int J Environ Res Public Health 14, no. 10 (2017).
Laber, Eric B., Ying-Qi Zhao, Todd Regh, Marie Davidian, Anastasios Tsiatis, Joseph B. Stanford, Donglin Zeng, Rui Song, and Michael R. Kosorok. "Using pilot data to size a two-arm randomized trial to find a nearly optimal personalized treatment strategy." Stat Med 35, no. 8 (2016): 1245-56.
Zhang, Yichi, Eric B. Laber, Anastasios Tsiatis, and Marie Davidian. "Using decision lists to construct interpretable and parsimonious treatment regimes." Biometrics 71, no. 4 (2015): 895-904.
Viele, Kert, Scott Berry, Beat Neuenschwander, Billy Amzal, Fang Chen, Nathan Enas, Brian Hobbs, Joseph G. Ibrahim, Nelson Kinnersley, Stacy Lindborg et al. "Use of historical control data for assessing treatment effects in clinical trials." Pharm Stat 13, no. 1 (2014): 41-54.
Barry, William T., Charles M. Perou, Kelly P Marcom, Lisa A. Carey, and Joseph G. Ibrahim. "The use of Bayesian hierarchical models for adaptive randomization in biomarker-driven phase II studies." J Biopharm Stat 25, no. 1 (2015): 66-88.
Ghosh, Arpita, Fred A. Wright, and Fei Zou. "Unified Analysis of Secondary Traits in Case-Control Association Studies." J Am Stat Assoc 108, no. 502 (2013).
Liu, Yulun, Yong Chen, and Haitao Chu. "A unification of models for meta-analysis of diagnostic accuracy studies without a gold standard." Biometrics 71, no. 2 (2015): 538-47.
Verde, Audrey R., Francois Budin, Jean-Baptiste Berger, Aditya Gupta, Mahshid Farzinfar, Adrien Kaiser, Mihye Ahn, Hans Johnson, Joy Matsui, Heather C. Hazlett et al. "UNC-Utah NA-MIC framework for DTI fiber tract analysis." Front Neuroinform 7 (2014): 51.
Jung, Sin-Ho, Yong Chen, and Hongshik Ahn. "Type I error control for tree classification." Cancer Inform 13, no. Suppl 7 (2014): 11-8.
Love, Michael I., Charlotte Soneson, Peter F. Hickey, Lisa K. Johnson, Tessa N Pierce, Lori Shepherd, Martin Morgan, and Rob Patro. "Tximeta: Reference sequence checksums for provenance identification in RNA-seq." PLoS Comput Biol 16, no. 2 (2020): e1007664.
Ivanova, Anastasia, and Allison M. Deal. "Two-stage design for phase II oncology trials with relaxed futility stopping." Stat Interface 9, no. 1 (2016): 93-98.
Shin, Seung Jun, Yichao Wu, and Hao Helen Zhang. "Two-Dimensional Solution Surface for Weighted Support Vector Machines." J Comput Graph Stat 23, no. 2 (2014): 383-402.
Li, Yimei, John H. Gilmore, Jiaping Wang, Martin Styner, Weili Lin, and Hongtu Zhu. "TwinMARM: two-stage multiscale adaptive regression methods for twin neuroimaging data." IEEE Trans Med Imaging 31, no. 5 (2012): 1100-12.
Ni, Ai, and Jianwen Cai. "Tuning Parameter Selection in Cox Proportional Hazards Model with a Diverging Number of Parameters." Scand Stat Theory Appl 45, no. 3 (2018): 557-570.

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