Parameter estimation bias of dichotomous logistic item response theory models using different variables
Yükleniyor...
Dosyalar
Tarih
2019
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Advanced Engineering and Science
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
The aim of this study was to examine the precision of item parameter
estimation in different sample sizes and test lengths under three parameter
logistic model (3PL) item response theory (IRT) model, where the trait
measured by a test was not normally distributed or had a skewed
distribution.In the study, number of categories (1-0), and item response
model were identified as fixed conditions, and sample size, test length
variables, and the ability distributions were selected as manipulated
conditions. This is a simulation study. So data simulation and data analysis
were done via packages in the R programming language. Results of the study
showed that item parameter estimations performed under normal distribution
were much stronger and bias-free compared to non-normal distribution.
Moreover, the sample size had some limited positive effect on parameter
estimation. However, the test length had no effect parameter estimation. As a
result the importance of normality assumptions for IRT models were
highlighted and findings were discussed based on relevant literature.
Açıklama
Anahtar Kelimeler
Ability distribution, Item response theory, Parameter recovery, Simulation
Kaynak
International Journal of Evaluation and Research in Education
WoS Q Değeri
Scopus Q Değeri
Q3
Cilt
8
Sayı
3
