This paper focuses on studying the relationships among a set of categorical (ordinal) variables collected in a contingency table. Besides the marginal and conditional (in)dependencies, thoroughly analyzed in the literature, we consider the context-specific independencies holding only in a subspace of the outcome space of the conditioning variables. To this purpose we consider the hierarchical multinomial marginal models and we provide several original results about the representation of context-specific independencies through these models. The theoretical results are supported by an application concerning the innovation degree of Italian enterprises.
Nicolussi, F., Cazzaro, M. (2020). Context-specific independencies in hierarchical multinomial marginal models. STATISTICAL METHODS & APPLICATIONS, 29(4), 767-786 [10.1007/s10260-019-00503-8].
Context-specific independencies in hierarchical multinomial marginal models
Nicolussi, F
;Cazzaro, M
2020
Abstract
This paper focuses on studying the relationships among a set of categorical (ordinal) variables collected in a contingency table. Besides the marginal and conditional (in)dependencies, thoroughly analyzed in the literature, we consider the context-specific independencies holding only in a subspace of the outcome space of the conditioning variables. To this purpose we consider the hierarchical multinomial marginal models and we provide several original results about the representation of context-specific independencies through these models. The theoretical results are supported by an application concerning the innovation degree of Italian enterprises.File | Dimensione | Formato | |
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