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

Year 2018, Volume: 5 Issue: 2, 263 - 273, 19.05.2018

Hakan Koğar

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 (positively skewed, normal,
negatively skewed), three response formats (three-, five- and seven-level
likert) and four different sample sizes (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

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

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 (positively skewed, normal, negatively skewed), three response formats (three-, five- and seven-level likert) and four different sample sizes (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

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