Abstract
Research problems related to individuals’ behaviors and attitudes requires examining inevitable changes over time. Because learning by nature implies change, analysis of longitudinal data becomes an important topic especially in the field of education. In this article, linear changes of a particular attribute over time was studied in the framework of the second order latent growth models by using data generated from Monte Carlo simulation. All analyses were performed by using Mplus 5.1 software. Related Mplus syntaxes were introduced and the interpretation of the model parameters was discussed. Additionally, it was explained how to study measurement equivalence in these models. Analyses were performed in three steps: (1) basic latent growth model, (2) latent growth model with weak measurement equivalence, and (3) strong measurement equivalence.
Keywords: Second order latent growth models, measurement equivalence, Monte Carlo simulation
Copyright and license
Copyright © 2011 The Author(s). This is an open access article distributed under the Creative Commons Attribution License (CC BY), which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is properly cited.
How to cite
Dural, S., Somer, O., Korkmaz, M., Can, S., & Öğretmen, T. (2011). Second Order Latent Growth Models and Measurement Equivalence. Education and Science, 36(161). https://educationandscience.ted.org.tr/article/view/952