SEDA DURAL ÇETİNKAYA, Oya SOMER, MEDİHA KORKMAZ, SEDA CAN, TUNCAY ÖĞRETMEN

Zamana bağlı değişimin incelenmesi: Örtük gelişme modelleri

Bu makalenin amacı, son yıllarda boylamsal ve/veya tekrarlı ölçümlerin zaman içerisindeki değişimlerinin incelenmesinde, varyans analizi gibi klasik yöntemlere alternatif olarak önerilen Yapısal Eşitlik Modellemeleri kapsamında yer alan Örtük Gelişme Modelleri’nin Monte Carlo simülasyon yaklaşımı kullanılarak çalışılmasıdır. Bu çerçevede, simülasyon verileri üzerinden modelin tanıtımı yapılmış ve bulguların yorumlanması üzerinde durulmuştur. Ayrıca 30, 50, 100 ve 200 olmak üzere dört farklı örneklem büyüklüğüne sahip simülasyon verileri kullanılarak örneklem büyüklüğünün testin gücü ve parametre tahminleri üzerindeki etkileri incelenmiştir. Bu amaç doğrultusunda sunulan makale çerçevesinde, (1) Monte Carlo simülasyonu yapılarak analizlerde kullanılacak verilerin üretilmesi, (2) koşulsuz ve koşullu modellerin parametre tahminleri yapılarak sonuçların yorumlanması ve (3) örneklem büyüklüğünün parametre tahmin yanlılığı, standart hata yanlılığı, kapsama alanı ve yüzde anlamlılık katsayısı üzerindeki etkisinin incelenmesi olmak üzere üç aşamalı bir işlem yolu izlenmiştir. Çalışmada sunulan analizlerin tümünde Mplus 5.1 programı kullanılmıştır. Sonuçlar, Örtük Gelişme Modelleri’nin avantaj ve dezavantajları, örneklem büyüklüğünün etkileri ve Mplus programının kullanım avantajları çerçevesinde tartışılmıştır.

An analysis of change over time: Latent growth models

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 fi ndings 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 fi ndings 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.

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