A Statistical Analysis of Brain Morphology Using Wild Bootstrapping. - Hongtu Zhu; Joseph G. Ibrahim; Niansheng Tang; D. B. Rowe; Xuejun Hao; Ravi Bansal; Bradley S. Peterson (IEEE Trans. Medical Imaging, 2007)

A Note on the Validity of Statistical Bootstrapping for Estimating the Uncertainty of Tensor Parameters in Diffusion Tensor Images. - Ying Yuan; Hongtu Zhu; Joseph G. Ibrahim; Weili Lin; Bradley S. Peterson (IEEE Trans. Medical Imaging, 2008)

MARM: Multiscale Adaptive Regression Models for Neuroimaging Data. - Hongtu Zhu; Yimei Li; Joseph G. Ibrahim; Weili Lin; Dinggang Shen (IPMI, 2009)

Intrinsic Regression Models for Manifold-Valued Data. - Xiaoyan Shi; Martin Styner; Jeffrey A. Lieberman; Joseph G. Ibrahim; Weili Lin; Hongtu Zhu (MICCAI (1), 2009)

RADTI: regression analyses of diffusion tensor images. - Yimei Li; Hongtu Zhu; Yasheng Chen; Joseph G. Ibrahim; Hongyu An; Weili Lin; Colin Hall; Dinggang Shen (Image Processing, 2009)

A hierarchical model for incomplete alignments in phylogenetic inference. - Fuxia Cheng; Stefanie Hartmann; Mayetri Gupta; Joseph G. Ibrahim; Todd J. Vision (Bioinform., 2009)

Maximum likelihood inference for the Cox regression model with applications to missing covariates. - Ming-Hui Chen; Joseph G. Ibrahim; Qi-Man Shao (J. Multivar. Anal., 2009)

Differential expression analysis with global network adjustment. - Jonathan A. Gelfond; Joseph G. Ibrahim; Mayetri Gupta; Ming-Hui Chen; Jannine D. Cody (BMC Bioinform., 2013)

HFPRM: Hierarchical Functional Principal Regression Model for Diffusion Tensor Image Bundle Statistics. - Jingwen Zhang; Chao Huang 005; Joseph G. Ibrahim; Shaili Jha; Rebecca C. Knickmeyer; John H. Gilmore; Martin Styner; Hongtu Zhu (IPMI, 2017)

Bayesian longitudinal low-rank regression models for imaging genetic data from longitudinal studies. - Zhaohua Lu; Zakaria Khondker; Joseph G. Ibrahim; Yue Wang 066; Hongtu Zhu (NeuroImage, 2017)

A Powerful Global Test Statistic for Functional Statistical Inference. - Jingwen Zhang; Joseph G. Ibrahim; Tengfei Li 001; Hongtu Zhu (AAAI, 2019)

Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences. - Anqi Zhu; Joseph G. Ibrahim; Michael I. Love (Bioinform., 2019)

Handling Non-ignorably Missing Features in Electronic Health Records Data Using Importance-Weighted Autoencoders. - David K. Lim; Naim U. Rashid; Junier B. Oliva; Joseph G. Ibrahim (CoRR, 2021)

BayesCTDesign: An R Package for Bayesian Trial Design Using Historical Control Data. - Barry Eggleston; Joseph G. Ibrahim; Becky McNeil; Diane Catellier (J. Stat. Softw., 2021)

metapack: An R Package for Bayesian Meta-Analysis and Network Meta-Analysis with a Unified Formula Interface. - Daeyoung Lim; Ming-Hui Chen; Joseph G. Ibrahim; Sungduk Kim; Arvind K. Shah; Jianxin Lin (R J., 2022)

BayesPPD: An R Package for Bayesian Sample Size Determination Using the Power and Normalized Power Prior for Generalized Linear Models. - Yueqi Shen; Matthew A. Psioda; Joseph G. Ibrahim (R J., 2023)

Deeply Learned Generalized Linear Models with Missing Data. - David K. Lim; Naim U. Rashid; Junier B. Oliva; Joseph G. Ibrahim (J. Comput. Graph. Stat., 2024)

glmmPen: High Dimensional Penalized Generalized Linear Mixed Models. - Hillary M. Heiling; Naim U. Rashid; Quefeng Li; Joseph G. Ibrahim (R J., 2024)