Effects of Various Simulation Conditions on Latent-Trait Estimates: A Simulation Study

Authors : Hakan Koğar

Pages : 263-273

View : 26 | Download : 11

Publication Date : 2018-05-19

Article Type : Research Paper

Abstract :The aim of this simulation study, determine the relationship between true latent scores and estimated latent scores by including various control variables and different statistical models. The study also aimed to compare the statistical models and determine the effects of different distribution types, response formats and sample sizes on latent score estimations. 108 different data bases, comprised of three different distribution types insert ignore into journalissuearticles values(positively skewed, normal, negatively skewed);, three response formats insert ignore into journalissuearticles values(three-, five- and seven-level likert); and four different sample sizes insert ignore into journalissuearticles values(100, 250, 500, 1000); were used in the present study. Results show that, distribution types and response formats, in almost all simulations, have significant effect on determination coefficients. When the general performance of the models are evaluated, it can be said that MR and GRM display a better performance than the other models. Particularly in situations when the distribution is either negatively or positively skewed and when the sample size is small, these models display a rather good performance.
Keywords : Item response theory, Classical test theory, Factor analysis, Latent trait scores, Data simulation