Lin, Li-An; Luo, Sheng; Davis, Barry R (2018) Bayesian regression model for recurrent event data with event-varying covariate effects and event effect. J Appl Stat 45:1260-1276
|
Yang, Chengwu; Vrana, Kent E (2018) Rescuing Suboptimal Patient-Reported Outcome Instrument Data in Clinical Trials: A New Strategy. Healthcare (Basel) 6:
|
Zhu, Huirong; DeSantis, Stacia M; Luo, Sheng (2018) Joint modeling of longitudinal zero-inflated count and time-to-event data: A Bayesian perspective. Stat Methods Med Res 27:1258-1270
|
Luthra, Nijee S; Kim, Soeun; Zhang, Yunxi et al. (2018) Characterization of vitamin D supplementation and clinical outcomes in a large cohort of early Parkinson's disease. J Clin Mov Disord 5:7
|
Li, Kan; O'Brien, Richard; Lutz, Michael et al. (2018) A prognostic model of Alzheimer's disease relying on multiple longitudinal measures and time-to-event data. Alzheimers Dement 14:644-651
|
Chen, Geng; Luo, Sheng (2018) Bayesian Hierarchical Joint Modeling Using Skew-Normal/Independent Distributions. Commun Stat Simul Comput 47:1420-1438
|
Leehey, Maureen; Luo, Sheng; Sharma, Saloni et al. (2017) Association of metabolic syndrome and change in Unified Parkinson's Disease Rating Scale scores. Neurology 89:1789-1794
|
Li, Liang; Luo, Sheng; Hu, Bo et al. (2017) Dynamic Prediction of Renal Failure Using Longitudinal Biomarkers in a Cohort Study of Chronic Kidney Disease. Stat Biosci 9:357-378
|
Wang, Jue; Luo, Sheng; Li, Liang (2017) DYNAMIC PREDICTION FOR MULTIPLE REPEATED MEASURES AND EVENT TIME DATA: AN APPLICATION TO PARKINSON'S DISEASE. Ann Appl Stat 11:1787-1809
|
Li, Kan; Luo, Sheng (2017) Functional joint model for longitudinal and time-to-event data: an application to Alzheimer's disease. Stat Med 36:3560-3572
|
Showing the most recent 10 out of 100 publications