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ORCIDJoseph G. Ibrahim
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2020 – today
- 2024
[j12]David K. Lim
, Naim U. Rashid, Junier B. Oliva, Joseph G. Ibrahim:
Deeply Learned Generalized Linear Models with Missing Data. J. Comput. Graph. Stat. 33(2): 638-650 (2024)- [j11]Hillary M. Heiling, Naim U. Rashid, Quefeng Li, Joseph G. Ibrahim:
glmmPen: High Dimensional Penalized Generalized Linear Mixed Models. R J. 15(4): 106-128 (2024) - 2023
- [j10]Yueqi Shen, Matthew A. Psioda, Joseph G. Ibrahim:
BayesPPD: An R Package for Bayesian Sample Size Determination Using the Power and Normalized Power Prior for Generalized Linear Models. R J. 14(4): 335-351 (2023) - 2022
- [j9]Daeyoung Lim, Ming-Hui Chen, Joseph G. Ibrahim, Sungduk Kim, Arvind K. Shah, Jianxin Lin:
metapack: An R Package for Bayesian Meta-Analysis and Network Meta-Analysis with a Unified Formula Interface. R J. 14(3): 142-161 (2022) - [i2]David K. Lim, Naim U. Rashid, Junier B. Oliva, Joseph G. Ibrahim:
Deeply-Learned Generalized Linear Models with Missing Data. CoRR abs/2207.08911 (2022) - 2021
- [j8]Barry Eggleston, Joseph G. Ibrahim, Becky McNeil, Diane Catellier:
BayesCTDesign: An R Package for Bayesian Trial Design Using Historical Control Data. J. Stat. Softw. 100(21) (2021) - [i1]David K. Lim, Naim U. Rashid, Junier B. Oliva, Joseph G. Ibrahim:
Handling Non-ignorably Missing Features in Electronic Health Records Data Using Importance-Weighted Autoencoders. CoRR abs/2101.07357 (2021)
2010 – 2019
- 2019
- [j7]Anqi Zhu, Joseph G. Ibrahim, Michael I. Love:
Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences. Bioinform. 35(12): 2084-2092 (2019) - [c5]Jingwen Zhang, Joseph G. Ibrahim, Tengfei Li, Hongtu Zhu:
A Powerful Global Test Statistic for Functional Statistical Inference. AAAI 2019: 5765-5772 - 2017
- [j6]Zhaohua Lu, Zakaria Khondker, Joseph G. Ibrahim, Yue Wang, Hongtu Zhu:
Bayesian longitudinal low-rank regression models for imaging genetic data from longitudinal studies. NeuroImage 149: 305-322 (2017) - [c4]Jingwen Zhang, Chao Huang, Joseph G. Ibrahim, Shaili Jha, Rebecca C. Knickmeyer, John H. Gilmore, Martin Styner, Hongtu Zhu:
HFPRM: Hierarchical Functional Principal Regression Model for Diffusion Tensor Image Bundle Statistics. IPMI 2017: 478-489 - 2013
- [j5]Jonathan A. Gelfond, Joseph G. Ibrahim, Mayetri Gupta, Ming-Hui Chen, Jannine D. Cody:
Differential expression analysis with global network adjustment. BMC Bioinform. 14: 258 (2013)
2000 – 2009
- 2009
- [j4]Fuxia Cheng, Stefanie Hartmann, Mayetri Gupta, Joseph G. Ibrahim, Todd J. Vision:
A hierarchical model for incomplete alignments in phylogenetic inference. Bioinform. 25(5): 592-598 (2009) - [j3]Ming-Hui Chen, Joseph G. Ibrahim, Qi-Man Shao:
Maximum likelihood inference for the Cox regression model with applications to missing covariates. J. Multivar. Anal. 100(9): 2018-2030 (2009) - [c3]Hongtu Zhu, Yimei Li, Joseph G. Ibrahim, Weili Lin, Dinggang Shen:
MARM: Multiscale Adaptive Regression Models for Neuroimaging Data. IPMI 2009: 314-325 - [c2]Xiaoyan Shi, Martin Styner, Jeffrey A. Lieberman, Joseph G. Ibrahim, Weili Lin, Hongtu Zhu:
Intrinsic Regression Models for Manifold-Valued Data. MICCAI (1) 2009: 192-199 - [c1]Yimei Li, Hongtu Zhu, Yasheng Chen, Joseph G. Ibrahim, Hongyu An, Weili Lin, Colin Hall, Dinggang Shen:
RADTI: regression analyses of diffusion tensor images. Image Processing 2009: 72591C - 2008
- [j2]Ying Yuan, Hongtu Zhu, Joseph G. Ibrahim, Weili Lin, Bradley S. Peterson:
A Note on the Validity of Statistical Bootstrapping for Estimating the Uncertainty of Tensor Parameters in Diffusion Tensor Images. IEEE Trans. Medical Imaging 27(10): 1506-1514 (2008) - 2007
- [j1]Hongtu Zhu, Joseph G. Ibrahim, Niansheng Tang, D. B. Rowe, Xuejun Hao, Ravi Bansal, Bradley S. Peterson:
A Statistical Analysis of Brain Morphology Using Wild Bootstrapping. IEEE Trans. Medical Imaging 26(7): 954-966 (2007)
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