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Latent structureItem response theory / latent variable multilevel models

Multilevel Item Response Theory

Multilevel item response theory (MLIRT) joins two powerful frameworks: an IRT measurement model that turns item responses into a latent ability, and a multilevel structural model that explains how that ability varies across nested groups such as classrooms, schools, or countries. Instead of first scoring a test and then running a multilevel regression on the scores, MLIRT does both at once, so that measurement error in ability is properly carried into the group-level analysis. It is the rigorous way to study how student and school characteristics relate to a latent trait measured by a test.

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Fontes

  1. Fox, J.-P. (2010). Bayesian Item Response Modeling: Theory and Applications. Springer. DOI: 10.1007/978-1-4419-0742-4
  2. De Boeck, P., & Wilson, M. (Eds.). (2004). Explanatory Item Response Models: A Generalized Linear and Nonlinear Approach. Springer. ISBN: 9780387402758

Como citar esta página

ScholarGate. (2026, June 22). Multilevel Item Response Theory Models for Clustered Test Data. ScholarGate. https://scholargate.app/pt/education/multilevel-irt

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ScholarGateMultilevel Item Response Theory (Multilevel Item Response Theory Models for Clustered Test Data). Recuperado em 2026-06-24 de https://scholargate.app/pt/education/multilevel-irt · Conjunto de dados: https://doi.org/10.5281/zenodo.20539026