This chapter is about methodological advances in the statistical analysis of developmental data that have specific promise for addressing questions about specific learning disabilities (SLD). These methods are especially well suited to capturing information about the nature of development and about individual differences in developmental processes, including differences of either a quantitative or qualitative nature. Although these methods are complex and can be used in quite sophisticated ways to address difficult questions, they can be explained in a conceptual way that is nonetheless rigorous and reasonably comprehensive. It is the goal of this chapter to provide such an introduction. At the same time, discussion of SLD and of these new statistical methods is made easier if readers have a firm understanding about the nature of measurement in psychology and education, and understand the central importance of both measurement theory and latent variables to psychological explanations. For that reason, this chapter is organized so as to first provide the reader some background on measurement in psychological science and on SLD. Subsequently, we will examine some specific advances in statistical modeling of developmental data, along with some examples to help the reader develop a clearer understanding of the models and their implications for research on SLD.