In this session, speakers will focus on recent developments in novel methods proposed for longitudinal data and joint modeling of survival and longitudinal data. 

Increasingly, with the ease of data collection due to technological developments, we need more advanced methods to analyze complex high-dimensional correlated data. In this session, speakers will focus on recent developments in novel methods proposed for longitudinal data and joint modeling of survival and longitudinal data. The methods that will be discussed in the session will include nonparametric methods and Bayesian inference for joint modeling of survival and longitudinal data, prediction of discrete longitudinal outcomes in heterogeneous populations, and time series clustering. Application examples will come from medical data and industrial engineering. This session is proposed by Drs. Esra Kurum (University of California, Riverside) and Elizabeth Juarez-Colunga (University of Colorado).

Organiser: Dr Esra Kurum 

Chair: Dr Esra Kurum 

Speaker: Kristen Miller

Speaker: Debaleena Sain 

Speaker: Prof. Saman Muthukumarana 

Speaker: Esra Kurum