Publications

Filters: Keyword is Monte Carlo Method and Author is Ibrahim, Joseph G  [Clear All Filters]
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Monte Carlo Method
Ibrahim, Joseph G., Sungduk Kim, Ming-Hui Chen, Arvind K. Shah, and Jianxin Lin. "Bayesian multivariate skew meta-regression models for individual patient data." Stat Methods Med Res 28, no. 10-11 (2019): 3415-3436.
Guo, Ruixin, Hongtu Zhu, Sy-Miin Chow, and Joseph G. Ibrahim. "Bayesian lasso for semiparametric structural equation models." Biometrics 68, no. 2 (2012): 567-77.
Lu, Zhao-Hua, Zakaria Khondker, Joseph G. Ibrahim, Yue Wang, and Hongtu Zhu. "Bayesian longitudinal low-rank regression models for imaging genetic data from longitudinal studies." Neuroimage 149 (2017): 305-322.
Ibrahim, Joseph G., Ming-Hui Chen, Amy H Xia, and Thomas Liu. "Bayesian meta-experimental design: evaluating cardiovascular risk in new antidiabetic therapies to treat type 2 diabetes." Biometrics 68, no. 2 (2012): 578-86.
Chen, Qingxia, Ming-Hui Chen, David Ohlssen, and Joseph G. Ibrahim. "Bayesian modeling and inference for clinical trials with partial retrieved data following dropout." Stat Med 32, no. 24 (2013): 4180-95.
Kim, Sungduk, Ming-Hui Chen, Joseph G. Ibrahim, Arvind K. Shah, and Jianxin Lin. "Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol-lowering drugs." Stat Med 32, no. 23 (2013): 3972-90.
Diao, Guoqing, Guanghan F. Liu, Donglin Zeng, William Wang, Xianming Tan, Joseph F. Heyse, and Joseph G. Ibrahim. "Efficient methods for signal detection from correlated adverse events in clinical trials." Biometrics 75, no. 3 (2019): 1000-1008.
May, Ryan C., Joseph G. Ibrahim, and Haitao Chu. "Maximum likelihood estimation in generalized linear models with multiple covariates subject to detection limits." Stat Med 30, no. 20 (2011): 2551-61.