The core of life course or lifespan research consists in studying how individual trajectories are shaped and unfold over time, from conception to death (Baltes 1987). Two concepts are fundamental in this endeavor: stability and change. Indeed, while certain individual characteristics remain constant across one's lifespan (e.g., sex, ethnicity), others undergo profound change, to the point that they might mutate into other characteristics (e.g., health, cognitive capacities). Such changes need not be independent of each other. They may simply co-occur, in the sense that while they happen simultaneously, it is hard to infer causality mechanisms between them. They may also be intrinsically related, where one change process is a necessary antecedent of the other, which becomes the consequence. The empirical study of lifespan development necessitates hence statistical models capable, at the very least, of (a) estimating constancy and change in informa- tion from a collection of observed measurements and (b) assessing degrees of interrelationships among constant and changing characteristics. Moreover, in a contextual paradigm typical of life course research, it is also highly desirable to ascertain which characteristics are intrinsic to the individual and which are influenced by, or stem from, external factors. Thus, the statistical models adopted in life course research face a number of challenging questions, which in turn can only be met with an appropriate data collection methodology.