The study of (in)dependence relationships among a set of categorical variables collected in a contingency table is an amply topic. In this work we want to focus on the so called context-specific independence where the conditional independence holds only in a subspace of the outcome space. The main aspects that we introduce concern the definition in the same model of marginal, conditional and context-specific independencies, through the marginal models. Furthermore, we investigate how it is possible to test these context-specific independencies when there are ordinal variables. Finally, we propose a graphical representation of all the considered independencies taking advantages from the chain graph model. We show the results on an application on ”The Italian Innovation Survey” of Istat (2012).

Context-specific independence in innovation study / F. Nicolussi, M. Cazzaro - In: Proceedings of the 17th ASMDA international conference / [a cura di] C.H. Skiadas. - [s.l] : ISAST, 2017. - ISBN 9786185180225. (( Intervento presentato al 17. convegno ASMDA tenutosi a London nel 2017.

Context-specific independence in innovation study

F. Nicolussi;
2017

Abstract

The study of (in)dependence relationships among a set of categorical variables collected in a contingency table is an amply topic. In this work we want to focus on the so called context-specific independence where the conditional independence holds only in a subspace of the outcome space. The main aspects that we introduce concern the definition in the same model of marginal, conditional and context-specific independencies, through the marginal models. Furthermore, we investigate how it is possible to test these context-specific independencies when there are ordinal variables. Finally, we propose a graphical representation of all the considered independencies taking advantages from the chain graph model. We show the results on an application on ”The Italian Innovation Survey” of Istat (2012).
Context-specific independence, ordinal variables, graphical models, innovation
Settore SECS-S/01 - Statistica
2017
Book Part (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/576118
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