Browsing by Author "Ogretmen, Tuncay"

Now showing 1 - 2 of 2

Citation - Scopus: 1
An Analysis of Change Over Time: Latent Growth Models
(Turkish Psychologists Assoc, 2010) Dural, Seda; Somer, Oya; Korkmaz, Mediha; Can, Seda; Ogretmen, Tuncay
Latent Growth Models which are used in understanding how individuals change over time have been a topic of intense interest among the researchers during the past two decades. These models in the framework of Structural Equation Modeling have been recommended as an alternative to classical methods such as analysis of variance. In this study, Latent Growth Models were introduced by using a Monte Carlo simulation approach and the interpretation of the findings was discussed. In addition, the effect of different sample sizes (30, 50, 100, and 200) on power and parameter estimates were examined. For this purpose; (1) data generation was performed with Monte Carlo simulation, (2) the parameters of unconditional and conditional models were estimated and the findings were discussed and (3) the effect of sample size on parameter estimates, standard errors, coverage and power was studied. All of the analyses were performed by using Mplus 5.1 software. Results were discussed in the context of advantages and disadvantages of Latent Growth Models, and the effect of sample size.
Second Order Latent Growth Models and Measurement Equivalence
(Turkish Education Assoc, 2011) Dural, Seda; Somer, Oya; Korkmaz, Mediha; Can, Seda; Ogretmen, Tuncay
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.