Bayesian Estimation of a Multidimensional Additive Graded Response Model for Correlated Traits. Issue 5 (27th May 2016)

• Record Type: Journal Article
• Authors: Martelli, Irene; Matteucci, Mariagiulia; Mignani, Stefania
• Is Part Of: Communications in statistics. Volume 45:Issue 5(2016)
• Page Start: 1636
• Page End: 1654
• Publication Date: 2016-05-27
• Subjects: Additive graded response model -- Item response theory -- MCMC; Primary 62C10 -- Secondary 62P25; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2014.932804
• Languages: English
• ISSNs: 0361-0918

Abstract

Abstract : The aim of the article is to propose a Bayesian estimation through Markov chain Monte Carlo of a multidimensional item response theory model for graded responses with an additive structure with correlated latent traits. A simulation study is conducted to evaluate the model parameter recovery under different conditions (sample size, test and subtest length, number of response categories, and correlation structure). The results show that the parameters are well reproduced when the sample size is sufficiently large ( n = 1, 000), while the worst recovery is observed for small sample size ( n = 500), and four response categories with a short number of test items.