Statistical methods for understanding cognitive growth: A review, a synthesis and an application

Methods for analysing data on cognitive growth are reviewed with emphasis given to the problems posed by scales which inevitably change over age. Multilevel growth curve and regression models are contrasted. A hybrid model is proposed which shares some of the advantages of these two approaches. The models are applied to a set of longitudinal data on mathematics growth from London primary school pupils. We find that conclusions about relative growth vary according to the scale adopted. Implications for the design and analysis of growth studies in psychology and education are discussed.