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12 - Modelling individual differences in change through latent variable growth and mixture growth modelling: basic principles and empirical examples

Published online by Cambridge University Press:  22 September 2009

Jan-eric Gustafsson
Affiliation:
Department of Education, Göteborg University, Sweden
Andreas Demetriou
Affiliation:
University of Cyprus
Athanassios Raftopoulos
Affiliation:
University of Cyprus
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Summary

Introduction

One of the most interesting and challenging tasks in the intersection of the fields of developmental psychology and differential psychology is the study of individual differences in development over time. To understand the nature of change during development, how change occurs, and what causes change it seems necessary not only to investigate general patterns, but also to take individual differences into account. There was, however, a time, not so long ago, when those with a focus on individual differences were reluctant to approach questions about change, because measurement of change was regarded as hopelessly difficult (e.g. Harris 1963). And those focusing on developmental problems have tended to neglect individual differences altogether.

During the last two decades the situation has changed dramatically for the better, however. One reason for this is the appearance of a new class of analytic techniques, namely growth curve models, or, for short, growth models. The basic idea of growth modelling is to describe developmental trajectories over time in terms of parsimonious models, the parameters of which may capture aspects such as initial level and rate of change. The analysis of growth curves was early identified as an important approach to research in developmental psychology (e.g. Bayley 1956). However, it was not until appropriate statistical techniques were developed in the 1980s that growth models were adopted on a wider scale in developmental psychology.

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