Research on Joint Model of Longitudinal Data

 
   Lead Investigator:    Yazhou Wu
   Institution      :    Wake Health
   E-Mail           :    yawu@wakehealth.edu
   Proposal ID      :    938



   Proposal Description:
   Our research aim is to explore a new kind joint statistical modeling method to  describe the complex relationship, concerning for the growth of whole and  individual differences as time changing for multiple longitudinal data.  Because, modeling and analysis of multiple longitudinal data with missing value  in biomedical big data is the key and difficult topic in the study of  statistical methodology, and traditional modeling and analysis methods have  been unable to describe and characterize the complex relationship of variables.  Through the analysis and application of the different data sets, confirm the  reliability, validity and robustness of the joint statistical modeling for  multiple longitudinal data using the new method, and we emphasis on discuss and  set up the statistical analysis strategies of multiple longitudinal data based  on the different response variable types, not negligible loss mechanism and  different analysis purposes.                                         Now, we are looking for a complex and big biomedical longitudinal data  #65288with multiple time points of repeated measurement data#65289to verify  the new statistical method. So, I want to request the whole the Uniform Data  Set (UDS) and its all follow-up visit data to apply to my research.         The main variables of interest include the baseline indicators, independent  variable and dependent variable (response variables), latent variables for some  cases.