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Parameter Recovery and Subpopulation Proficiency Estimation in Hierarchical Latent Regression Models IRT

Li, Deping; Oranje, Andreas; Jiang, Yanlin
Publication Year:
Report Number:
ETS Research Report
Document Type:
Page Count:
Subject/Key Words:
Hierarchical Model, Latent Regression, Item Response Theory (IRT)


Results show that regression effect estimates are similar between the HLRM and the LRM, in particular under small cluster variation. Similarly, student posterior mean estimates and marginal maximum likelihood mean estimates for student groups are comparable across the two model approaches. However, substantial differences are found for the residual variance estimates, the standard errors for regression effect estimates and related standard errors for group estimates, and for students posterior variance estimates. As expected, these differences are larger when the variation across clusters is larger, since a substantial portion of variance remains unexplained in LRM.

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