Bayesian logistic regression models for longitudinal data with time-dependent
covariates 
   Lead Investigator:    Maria Vazquez
   Institution      :    Arizona State University
   E-Mail           :    maria.vazquez@asu.edu
   Proposal ID      :    1186



   Proposal Description:
   Longitudinal data are frequently collected in Alzheimer's research. Such data sets contain both time-independent and time-dependent variables. The value of time dependent variables may change from one time point to another. The variation in time-dependent variables also influences the outcome of interest.  In this study, we will use a Bayesian logistic regression model that accounts for effects of time-dependent variables? change over time through a partitioned data matrix. The purpose of our study is to apply this model and illustrate its use and interpretation in Alzheimer's research when time-dependent variables are present.