skip to main content skip to footer

Hierarchical General Diagnostic Models GDM

von Davier, Matthias
Publication Year:
Report Number:
ETS Research Report
Document Type:
Page Count:
Subject/Key Words:
Latent Class Analysis, Multilevel Analysis, Item Response Models, General Diagnostic Model (GDM)


This paper introduces multilevel extensions for the general diagnostic model (GDM) following recent developments on extensions of latent class analysis (LCA) to hierarchical models. The GDM is based on LCA as well as discrete latent trait models and may be viewed as a general modeling framework for confirmatory multidimensional item response models. The multilevel extensions presented in this paper enable one to check the impact of clustered data, such as data for students within schools in large scale educational surveys, on the structural parameter estimates of the GDM. Moreover, the multilevel version of the GDM allows study of differences in skill distributions across these clusters.

Read More