Multi-display Implicit Development Models

Abstract

Research problems related to behaviors and attitudes of the individuals generally require examining change over time. Especially in psychology and education, to design such longitudinal research will make important contributions to enrich our knowledge in these fields. Some statistical methods like analysis of variance for repeated measures are commonly used in analysis of change. However, Latent Growth Models in the framework of Structural Equation Modeling offer important methodological improvements because it enables to develop hypotheses about change of latent variables' means over time and covariance structures of error terms. In the present study, it was aimed to investigate Latent Growth Models with multiple indicators by using data generated from Monte Carlo simulation and represent a demonstration for researchers. All analyses were performed by using Mplus 5.1 software. In this context, the growth model with multiple indicators was introduced, related Mplus syntaxes were explained and the interpretation of the model parameters was discussed.