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Naïve Tests of Basic Local Independence Model’s Invariance

Published online by Cambridge University Press:  28 April 2015

Debora de Chiusole ,
Luca Stefanutti ,
Pasquale Anselmi  and
Egidio Robusto
Debora de Chiusole*
Affiliation:
Università di Padova (Italy)
Luca Stefanutti
Affiliation:
Università di Padova (Italy)
Pasquale Anselmi
Affiliation:
Università di Padova (Italy)
Egidio Robusto
Affiliation:
Università di Padova (Italy)
*
*Correspondence concerning this article should be addressed to Debora de Chiusole. Università di Padova. FISPPA Department. Via Venenzia, 12. 35131. Padua (Italy). E- mail: deboratn@libero.it
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Abstract

The basic local independence model (BLIM) is a probabilistic model for knowledge structures, characterized by the property that lucky guess and careless error parameters of the items are independent of the knowledge states of the subjects. When fitting the BLIM to empirical data, a good fit can be obtained even when the invariance assumption is violated. Therefore, statistical tests are needed for detecting violations of this specific assumption. This work provides an extension to theoretical results obtained by de Chiusole, Stefanutti, Anselmi, and Robusto (2013), showing that statistical tests based on the partitioning of the empirical data set into two (or more) groups are not adequate for testing the BLIM’s invariance assumption. A simulation study confirms the theoretical results.

Keywords

knowledge space theorybasic local independence modelparameter invariance assumptionbipartition models
Type
Research Article
Information
The Spanish Journal of Psychology , Volume 18 , 2015 , E26
Copyright
Copyright © Universidad Complutense de Madrid and Colegio Oficial de Psicólogos de Madrid 2015 

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