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: Data Analysis and Applications 2 : Utilization of Results in Europe and Other Topics / [a cura di] C.H. Skiadas, J.R. Bozeman. - Prima edizione. - [s.l] : Wiley Blackwell Publishing, 2019 Feb. - ISBN 9781786304476. - pp. 3-14

Context-specific independence in innovation study

F. Nicolussi
Primo
;
2019

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
feb-2019
http://www.iste.co.uk/book.php?id=1462
Book Part (author)
File in questo prodotto:
File Dimensione Formato  
No17_Nicolussi Cazzaro.pdf

accesso aperto

Tipologia: Post-print, accepted manuscript ecc. (versione accettata dall'editore)
Dimensione 322.42 kB
Formato Adobe PDF
322.42 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/626288
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact