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Journals / Eğitim ve Bilim / 2011 / Cilt: 36 - Sayı: 161

Second order latend growth models and measurement equivalence

İkinci derece örtük gelişme modelleri ve ölçme eşdeğerliği

Oya SOMER
Mediha KORKMAZ
Seda DURAL
Seda CAN
Tucay ÖĞRETMEN
Pages
51–63
Publication Date
2022-10-18
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Analyses were performed in three steps: (1) basic latent growth model, (2) latent growth model with weak measurement equivalence, and (3) strong measurement equivalence.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Research problems related to individuals' behaviors and attitudes requires examining inevitable changes over time.
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Key Findings & Data: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.
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Conclusion & Impact:Analyses were performed in three steps: (1) basic latent growth model, (2) latent growth model with weak measurement equivalence, and (3) strong measurement equivalence.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

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.

Özet

Bireylerin davranış ya da tutumlarına ilişkin birçok araştırma problemi, zamandaki değişimin incelenmesini gerektirmektedir. Öğrenme konusunun, değişim kavramından ayrı tutulamayacağı göz önünde bulundurulduğunda, özellikle eğitim alanında bu tarz araştırmaların desenlenmesi, bu alandaki bilgilerimizin zenginleşmesine önemli katkılarda bulunacaktır. Bu çalışmada belirli bir özelliğin zaman içerisindeki doğrusal değişimi, Monte Carlo simülasyonu ile üretilmiş veri seti kullanılarak, ikinci derece örtük gelişme modelleri kapsamında ele alınmıştır. Analizlerin tümünde Mplus 5.1 programı kullanılmış; ilgili Mplus sentaksları açıklanmış ve model parametrelerinin yorumlanması üzerinde durulmuştur. Sunulan çalışmada ek olarak, örtük gelişme modellerinde ölçme eşdeğerliğinin nasıl test edileceği açıklanmıştır. Üretilen veri seti için analizler (1) temel örtük gelişme modeli, (2) örtük gelişme modelinde zayıf ölçme eşdeğerliği ve (3) örtük gelişme modelinde güçlü ölçme eşdeğerliği olmak üzere üç aşamada yapılmıştır.

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Cite This Article

SOMER, O., KORKMAZ, M., DURAL, S., CAN, S., ÖĞRETMEN, T. (2022). Second order latend growth models and measurement equivalence. Eğitim ve Bilim, Cilt: 36 - Sayı: 161, 51–63. https://ajindex.com/articles/497675

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