Collapsing over variables is a necessary procedure in much empirical research. Consequences are yet not always properly evaluated. In this paper, different definitions of collapsibility (simple, strict, strong, etc.) and corresponding necessary and sufficient conditions are reviewed and evaluated. We point out the relevance and limitations of the main contributions within a unifying interpretative framework. We deem such work to be useful since the debate on the topic has often developed in terms that are neither focused nor clear.

OLIVERI A, DE CANTIS S (2004). An overview of collapsibility. In BANKS D., HOUSE L., ARABIE P. AND GAUL W. EDS, . (a cura di), Classification, Clustering, and New Data Mining Applications (pp. 587-596). HEIDELBERG : Springer.

An overview of collapsibility

OLIVERI, Antonino Mario;DE CANTIS, Stefano
2004-01-01

Abstract

Collapsing over variables is a necessary procedure in much empirical research. Consequences are yet not always properly evaluated. In this paper, different definitions of collapsibility (simple, strict, strong, etc.) and corresponding necessary and sufficient conditions are reviewed and evaluated. We point out the relevance and limitations of the main contributions within a unifying interpretative framework. We deem such work to be useful since the debate on the topic has often developed in terms that are neither focused nor clear.
2004
OLIVERI A, DE CANTIS S (2004). An overview of collapsibility. In BANKS D., HOUSE L., ARABIE P. AND GAUL W. EDS, . (a cura di), Classification, Clustering, and New Data Mining Applications (pp. 587-596). HEIDELBERG : Springer.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/10929
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