ScholarGate
Assistent
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.

Åbn i MethodMindSnartAnvend, sammenlign, få vejledning
Værktøjer og ressourcer
Hent slides
Lær og udforsk
VideoSnart

Læs hele metoden

Kun for medlemmer

Log ind med en gratis konto for at læse dette afsnit.

Log ind

Metodekort

Nabolaget af beslægtede metoder — vælg en knude for at udforske.

Kilder

  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

Sådan citerer du denne side

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

Hvilken metode?

Stil denne metode ved siden af dens nærmeste slægtninge, og læs dem side om side — biblioteket lægger bøgerne på bordet; valget er dit.

Sammenlign side om side
ScholarGateMultilevel Item Response Theory (Multilevel Item Response Theory Models for Clustered Test Data). Hentet 2026-06-24 fra https://scholargate.app/da/education/multilevel-irt · Datasæt: https://doi.org/10.5281/zenodo.20539026