Literature DB >> 29881018

Marginalized Maximum Likelihood Estimation for the 1PL-AG IRT Model.

Ryoungsun Park1, Keenan A Pituch1, Jiseon Kim2, Barbara G Dodd1, Hyewon Chung3.   

Abstract

Marginal maximum likelihood estimation based on the expectation-maximization algorithm (MML/EM) is developed for the one-parameter logistic model with ability-based guessing (1PL-AG) item response theory (IRT) model. The use of the MML/EM estimator is cross-validated with estimates from NLMIXED procedure (PROC NLMIXED) in Statistical Analysis System. Numerical data are provided for comparisons of results from MML/EM and PROC NLMIXED.

Keywords:  1PL-AG; EM; IRT; MML; estimator

Year:  2015        PMID： 29881018      PMCID： PMC5978613          DOI： 10.1177/0146621615574694

Source DB:  PubMed          Journal:  Appl Psychol Meas        ISSN： 0146-6216


  2 in total

1.  Identification of the 1PL model with guessing parameter: parametric and semi-parametric results.

Authors:  Ernesto San Martín; Jean-Marie Rolin; Luis M Castro
Journal:  Psychometrika       Date:  2013-02-01       Impact factor: 2.500

2.  A nonlinear mixed model framework for item response theory.

Authors:  Frank Rijmen; Francis Tuerlinckx; Paul De Boeck; Peter Kuppens
Journal:  Psychol Methods       Date:  2003-06
  2 in total
  1 in total

1.  Bayesian Modal Estimation for the One-Parameter Logistic Ability-Based Guessing (1PL-AG) Model.

Authors:  Shaoyang Guo; Tong Wu; Chanjin Zheng; Yanlei Chen
Journal:  Appl Psychol Meas       Date:  2021-02-08
  1 in total

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