2005/02/14 by Wen‐Chung Wang, Wen-Chung Wang, Mark Wilson · 2 citations
Computer Science · Decision Sciences · Mathematics · Psychology · #Advanced Statistical Methods and Models #Advanced Statistical Modeling Techniques #Econometrics #Item response theory #Marginal likelihood #Mathematics #Maximum likelihood #Multinomial logistic regression #Polytomous Rasch model #Psychology #Psychometric Methodologies and Testing #Psychometrics #Rasch model #Statistics
paper · doi:10.1177/0146621604271053
openalex publication_date 2005/02/14 · crossref created 2005/02/14 · crossref issued 2005/03/01 · crossref published 2005/03/01 · crossref published-online 2005/03/01 · crossref published-print 2005/03/01 · openalex created_date 2025/10/10 · crossref deposited 2026/04/28 · crossref indexed 2026/08/02 · openalex updated_date 2026/08/02
The Rasch testlet model for both dichotomous and polytomous items in testlet-based tests is proposed. It can be viewed as a special case of the multidimensional random coefficients multinomial logit model (MRCMLM). Therefore, the estimation procedures for the MRCMLM can be directly applied. Simulations were conducted to examine parameter recovery under the dichotomous Rasch testlet model and the partial-credit testlet model. Results indicated that the item and person parameters as well as the random testlet effects could be recovered very accurately under all the simulated conditions. As sample sizes were increased, the root mean square errors of the estimates decreased to an acceptable level. An empirical example of an English test with 11 testlets was given. Index terms: multidimensional item response model, item bundle, marginal maximum likelihood estimation, parameter recovery.