Specifying Ability Growth Models Using a Multidimensional Item Response Model for Repeated Measures Categorical Ordinal Item Response Data

• Published in: Multivariate behavioral research Vol. 51; no. 4; pp. 569 - 580
• Main Authors: Paek, Insu, Li, Zhen, Park, Hyun-Jeong
• Format: Journal Article
• Language: English
• Published: United States Routledge 03.07.2016; Taylor & Francis Ltd
• Subjects: Algorithms; Aptitude Tests; Data Interpretation, Statistical; Employee testing; Humans; IRT for longitudinal data analysis; IRT for repeated measures data; IRT growth modeling; Language Tests; Linear Models; Measurement errors; multidimensional IRT; Multilevel Analysis - methods; Nonlinear Dynamics; Psychology, Child - methods; Research Design; Time Factors; IRT growth modeling; IRT for longitudinal data analysis; multidimensional IRT; IRT for repeated measures data
• ISSN: 0027-3171; 1532-7906
• DOI: 10.1080/00273171.2016.1178567

When categorical ordinal item response data are collected over multiple timepoints from a repeated measures design, an item response theory (IRT) modeling approach whose unit of analysis is an item response is suitable. This study proposes a few longitudinal IRT models and illustrates how a popular compensatory multidimensional IRT model can be utilized to formulate such longitudinal IRT models, which permits an investigation of ability growth at both individual and population levels. The equivalence of an existing multidimensional IRT model and those longitudinal IRT models is also elaborated so that one can make use of an existing multidimensional IRT model to implement the longitudinal IRT models.