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Explanatory Multidimensional Multilevel Random Item Response Model: an Application to Simultaneous Investigation of Word and Person Contributions to Multidimensional Lexical Representations

Overview
Journal Psychometrika
Specialty Social Sciences
Date 2013 Oct 5
PMID 24092491
Citations 6
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Abstract

This paper presents an explanatory multidimensional multilevel random item response model and its application to reading data with multilevel item structure. The model includes multilevel random item parameters that allow consideration of variability in item parameters at both item and item group levels. Item-level random item parameters were included to model unexplained variance remaining when item related covariates were used to explain variation in item difficulties. Item group-level random item parameters were included to model dependency in item responses among items having the same item stem. Using the model, this study examined the dimensionality of a person's word knowledge, termed lexical representation, and how aspects of morphological knowledge contributed to lexical representations for different persons, items, and item groups.

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References
1.
Gonzalez J, De Boeck P, Tuerlinckx F . A double-structure structural equation model for three-mode data. Psychol Methods. 2008; 13(4):337-53. DOI: 10.1037/a0013269. View

2.
Janssen R, De Boeck P . Confirmatory Analyses of Componential Test Structure Using Multidimensional Item Response Theory. Multivariate Behav Res. 2016; 34(2):245-68. DOI: 10.1207/S15327906Mb340205. View

3.
Hickendorff M, Heiser W, van Putten C, Verhelst N . Solution Strategies and Achievement in Dutch Complex Arithmetic: Latent Variable Modeling of Change. Psychometrika. 2009; 74(2):331-350. PMC: 2792350. DOI: 10.1007/s11336-008-9074-z. View

4.
Cho S, Partchev I, De Boeck P . Parameter estimation of multiple item response profile model. Br J Math Stat Psychol. 2011; 65(3):438-66. DOI: 10.1111/j.2044-8317.2011.02036.x. View

5.
Balota D, Yap M, Cortese M, Hutchison K, Kessler B, Loftis B . The English Lexicon Project. Behav Res Methods. 2007; 39(3):445-59. DOI: 10.3758/bf03193014. View