Comparison of Three Growth Modeling Techniques in the Multilevel Analysis of Longitudinal Academic Achievement Scores: Latent Growth Modeling, Hierarchical Linear Modeling, and Longitudinal Profile Analysis via Multidimensional Scaling

262 1 Longitudinal studies provide important sources of information when investigating how differences in various national and regional school policies, practices and compositional characteristics relate to differences in student achievement over a period of time. Therefore, it is not surprising that the use of growth modeling techniques in educational fields has rapidly increased. Recent years have produced a vast range of applications of structural equation modeling based (SEM) latent growth modeling (LGM) in applied longitudinal data analysis (Curran & Hussong, 2002;