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

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. I n 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.