Growth data and longitudinal data in general are often of an ordinal nature. For example, developmental stages may be classified into ordinal categories and behavioral variables repeatedly measured by discrete ordinal scales. Consider the data set presented in Table 15.1. This table contains information on marijuana use taken from five annual waves (1976–80) of the National Youth Survey (Elliot...

We consider dependent functional data that are correlated because of a longitudinal-based design: each subject is observed at repeated times and at each time a functional observation (curve) is recorded. We propose a novel parsimonious modeling framework for repeatedly observed functional observations that allows to extract low dimensional features. The proposed methodology accounts for the lon...