Inferences from Bootstrap Method for Ability Parameters in 2-Parameter Logistic Model

Year 2020, Volume: 16 Issue: 3, 333 - 338, 29.09.2020

Hülya Olmuş Ezgi Nazman

https://doi.org/10.18466/cbayarfbe.622868

Abstract

Ability parameter of persons/examinees estimates can
be obtained using Joint Maximum Likelihood (JML) estimation method in Item
Response Theory (IRT). However, JML estimates can be biased in some cases.
Although Bootstrap method has been considered for JML, existing studies remain
far from satisfactory with respect to the ability parameter estimation. This
research evaluate the performances of JML and Bootstrap estimates of ability
parameter in terms of Standard Error Measurement (SEM) in 2-Parameter Logistic
(2-PL) model conducting a detailed Monte Carlo simulation study. According to
the results, the average SEM estimates of Bootstrap method are less than the
average SEM estimates of JML in terms of the ability parameter.

Keywords

ability parameter, difficulty parameter, joint maximum likelihood estimation, discrimination parameter, two-parameter logistic model

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