Monte Carlo Simülasyon Yönteminde Tekrar Sayısı Klasik Test Kuramı Parametreleri İçin Kaç Olmalıdır?

Duygu Koçak

EN TR

What should be the number of replications in Monte Carlo Simulation Method for Classical Test Theory Parameters?

Abstract

The importance of the number of repetitions in the simulation studies to produce truth-reflecting results is indisputable. When a research is designed using Monte Carlo simulation technique, the number of repetitions is very important for the reliability and validity of the research results. However, there is no clear information on how many repetitions are sufficient. In this study, it is aimed to determine the effect of number of repetitions in Monte Carlo simulation method on item and test parameter estimations in Classical Test Theory and to determine the number of repetitions required. For this purpose, the data obtained by changing the number of replication under different conditions total variance ratio Cronbach's Alpha coefficient average of item discrimination and model-data-fit parameters were examined. This study is a Monte Carlo simulation study. In the research, R program “psyc” package was used for data generation and analysis. In this study, the number of items in a one-dimensional structure is fixed to 20, the response category is 5, and the sample size is changed to 100, 250, 500, 1000 and 3000. According to results of the study, in a study based on CTT, it is suggested that researchers produce data with 1000 replications when sample size is 100, 500 replications when sample size is 250, 250 replications when sample size is 500 and 100 replications when sample size is 1000 and 3000.

Keywords

Classical Test Theory,Monte Carlo,simulation,replication number

Monte Carlo Simülasyon Yönteminde Tekrar Sayısı Klasik Test Kuramı Parametreleri İçin Kaç Olmalıdır?

Öz

Simülasyon çalışmalarındaki tekrar sayısının gerçeği yansıtan sonuçlar üretmedeki önemi tartışılmazdır. Monte Carlo simülasyon tekniği kullanılarak bir araştırma tasarlandığında, tekrar sayısı araştırma sonuçlarının güvenilirliği ve geçerliliği için çok önemlidir. Ancak, kaç tekrarın yeterli olduğu konusunda net bir bilgi yoktur. Bu çalışmada, Klasik Test Teorisinde Monte Carlo simülasyon yöntemindeki tekrar sayısının madde ve test parametresi tahminlerine etkisini belirlemek ve gerekli tekrar sayısını belirlemek amaçlanmıştır. Bu amaçla, farklı koşullar altında tekrar sayısının değiştirilmesiyle elde edilen veriler toplam varyans oranı, Cronbach Alfa katsayısı, madde madde ortalama ortalaması ve model veri uyumu parametreleri incelenmiştir. Bu çalışma bir Monte Carlo simülasyon çalışmasıdır. Araştırmada veri üretimi ve analizi için R programı (2011) “psych” paketi kullanılmıştır. Bu çalışmada, tek boyutlu bir yapıdaki madde sayısı 20'ye, cevap kategorisi 5’e sabitlenerek, örneklem büyüklüğü 100, 250, 500, 1000 ve 3000 olarak değiştirilmiştir. Çalışmanın sonuçlarına göre, Klasik Test Kuramı'na dayalı bir çalışmada araştırmacıların, örneklem büyüklüğü 100 iken 1000 tekrar ile, örneklem büyüklüğü 250 iken 500 tekrar ile, örneklem 500 iken 250 tekrar ile ve örneklem büyüklüğü 1000 ve 3000 iken 100 tekrar ile veri üretmeleri önerilmektedir.

Anahtar Kelimeler

Klasik Test Kuramı,Monte Carlo,simülasyon,tekrar sayısı

Kaynakça

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Ayrıntılar

Birincil Dil

Türkçe

Konular

-

Bölüm

Araştırma Makalesi

Yazarlar

Duygu Koçak
0000-0003-3211-0426
Türkiye

Yayımlanma Tarihi

24 Haziran 2020

Gönderilme Tarihi

29 Ağustos 2019

Kabul Tarihi

20 Şubat 2020

Yayımlandığı Sayı

Yıl 2020 Cilt: 9 Sayı: 2

IZ

https://izlik.org/JA96TY72ZS

Kaynak Göster

RIS / Bibtex

APA

Koçak, D. (2020). Monte Carlo Simülasyon Yönteminde Tekrar Sayısı Klasik Test Kuramı Parametreleri İçin Kaç Olmalıdır? Cumhuriyet Uluslararası Eğitim Dergisi, 9(2), 410-429. https://izlik.org/JA96TY72ZS