Some models and their extensions for longitudinal analyses

Abstract: Longitudinal data frequently arises in various fields of sciences where individuals are measured in time. Statistically, analyzing these data has its challenges, because measurements may not be considered as independent. Research in this area has been quite lively since the mid-1960s when the so-called growth curve of Potthoff and Roy (1964) model was introduced. I will consider some extensions of the basic approaches that have been utilized for modeling longitudinal data. These will include multivariate extensions as far as utilizing of splines and finite mixtures. Illustrative real data examples play an important role in these considerations.