Alma Mater Digital Library

Edited by Documentary and Departmental Support

cambia la lingua in italiano
AMS Acta
ISSN: 2038-7954
Contributi di ricerca dell'Alma Mater Studiorum - Università di Bologna
Informazioni sul Single Sign-On di Ateneo Login for authors

The use of predicted values for item parameters in item response theory models: an application in intelligence tests

Matteucci, Mariagiulia ; Mignani, Stefania ; Veldkamp, Bernard P. (2012) The use of predicted values for item parameters in item response theory models: an application in intelligence tests. [Preprint]

Full text disponibile come:

[img]
Preview
PDF
Available under License Creative Commons Attribution Non-commercial (CC BY-NC 3.0).

237Kb

Abstract

In testing, item response theory models are widely used in order to estimate item parameters and individual abilities. However, even unidimensional models require a considerable sample size so that all parameters can be estimated precisely. The introduction of empirical prior information about candidates and items might reduce the number of candidates needed for parameter estimation. Using data for IQ measurement, this work shows how empirical information about items can be used effectively for item calibration and in adaptive testing. First, we propose multivariate regression trees to predict the item parameters based on a set of covariates related to the item solving process. Afterwards, we compare the item parameter estimation when tree fitted values are included in the estimation or when they are ignored. Model estimation is fully Bayesian, and is conducted via Markov chain Monte Carlo methods. The results are two-fold: a) in item calibration, it is shown that the introduction of prior information is effective with short test lengths and small sample sizes, b) in adaptive testing, it is demonstrated that the use of the tree fitted values instead of the estimated parameters leads to a moderate increase in the test length, but provides a considerable saving of resources.

Document type:Preprint
Uncontrolled Keywords:item response theory models, Bayesian estimation, multivariate regression trees, item calibration, adaptive testing, intelligence tests.
Subjects:Area 11 - Scienze storiche, filosofiche, pedagogiche e psicologiche > M-PSI/03 Psicometria
Area 13 - Scienze economiche e statistiche > SECS-S/01 Statistica
Area 13 - Scienze economiche e statistiche > SECS-S/05 Statistica sociale
DOI:10.6092/unibo/amsacta/3241
Depositato da:Mariagiulia Matteucci
Depositato il:13 Mar 2012 10:20
Last modified:05 Apr 2012 11:54

Solo per lo Staff dell Archivio: Gestione del documento