Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01NS043127-04
Application #
6786001
Study Section
Special Emphasis Panel (ZNS1-SRB-P (01))
Program Officer
Murphy, Diane
Project Start
2001-09-30
Project End
2006-07-31
Budget Start
2004-08-01
Budget End
2005-07-31
Support Year
4
Fiscal Year
2004
Total Cost
$390,650
Indirect Cost
Name
Medical University of South Carolina
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
183710748
City
Charleston
State
SC
Country
United States
Zip Code
29425
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
Li, Kan; Furr-Stimming, Erin; Paulsen, Jane S et al. (2017) Dynamic Prediction of Motor Diagnosis in Huntington's Disease Using a Joint Modeling Approach. J Huntingtons Dis 6:127-137
Lin, Li-An; Luo, Sheng; Chen, Bingshu E et al. (2017) Bayesian analysis of multi-type recurrent events and dependent termination with nonparametric covariate functions. Stat Methods Med Res 26:2869-2884
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