Multilevel IRT Model Assessment

Fox, Jean-Paul (2005) Multilevel IRT Model Assessment. In: New developments in categorical data analysis for the social and behavioral sciences. Lawrence Erlbaum, Mahwah, NJ [etc.], pp. 227-252. ISBN 9780805847284

PDF
Restricted to UT campus only
567Kb

Abstract:	Modelling complex cognitive and psychological outcomes in, for example, educational assessment led to the development of generalized item response theory (IRT) models. A class of models was developed to solve practical and challenging educational problems by generalizing the basic IRT models. An IRT model can be used to define a relation between observed categorical responses and an underlying latent trait, such as, ability or attitude. Subsequently, the latent trait variable can be seen as the outcome in a regression analysis. That is, a regression model defines the relation between the latent trait and the set of predictors. The combination of both models, a regression model imposed on the ability parameter in an IRT model, can be viewed as an extension to the class of IRT models.
Item Type:	Book Section
Copyright:	© 2005 Lawrence Erlbaum
Faculty:	Behavioural Sciences (BS)
Research Group:	Research Methodology, Measurement and Data Analysis (OMD)
Link to this item:	http://purl.utwente.nl/publications/59657
Export this item as:	BibTeX EndNote HTML Citation Reference Manager

Show download statistics for this publication

Repository Staff Only: item control page