Statistical Methodology in AIDS Research
Organizer: Ying Zhang, University of Iowa, ying-j-zhang@uiowa.edu
Chair: Ying Zhang, University of Iowa, ying-j-zhang@uiowa.edu
Description: This session features recent development in statistical methodology for HIV/AIDS research. It encompasses topics including joint modeling of longitudinal and event time data, survival data in Case-Cohort study, semiparametric models, bivariate survival data, and Bayesian inference with applications to various HIV/AIDS studies.
Speakers:
- Weighted Likelihood Method for Grouped Survival Data in Case-Cohort Studies with Application to HIV Vaccine Trials Bin Nan*, Zhiguo Li, and Peter Gilbert University of Michigan USA
- Joint inference for nonlinear mixed-effects models and time-to-event at the presence of missing data Lan Wu*, Joan Hu, and Hulin Wu University of British Columbia Canada
- Bayesian inference for group testing with application to California HIV data Hyonggin An*, Tae-Young Heo, and Jong-Min Kim Korea University South Korea
- HIV Dynamics Modeling Using Semiparameric NLME Models Jin-Ting Zhang* and Hulin Wu National University of Singapore Singapore
- Inference on Association Measure for Bivariate Hybrid Censoring Survival Data with Application to an HIV Study Ying Zhang*, Suhong Zhang, and Kathryn Chaloner University of Iowa, USA
