ABSTRACT
A fundamental concern for the social sciences is understanding how individuals change and in what way individuals change differently from each other (Baltes & Nesselroade, 1979). For example, Skibbe et al. (2008) found that the development of literacy skills during the elementary school years is characterized by decelerating growth with substantial heterogeneity in literacy skills at school entry and in the rate of growth. A further fundamental concern is understanding what relates to an individual’s change, from both causal and predictive perspectives. For example, Skibbe et al. found that language impairment status was predictive of the growth trajectory, such that children with a language impairment tended to start elementary school with lower literacy skills but gained the skills at a higher rate than did children displaying more typical development. Reaching such conclusions about change is not simple; there are challenges with theory development, study design, measurement, analysis, and interpretation. Traditional methods for analyzing change, such as repeated measures analysis of variance (ANOVA), have proved insufficient for addressing the many forms in which change can occur. Recent years have seen the development of several analytical frameworks that allow for a more direct expression of theories of change using a variety of study designs and forms of measurement. When utilized effectively, these frameworks can yield easily interpretable results that directly address theoretical questions about change. One example of such a framework is the multilevel growth framework described elsewhere in this volume (see Chapter 5).
