This chapter studies how the satisfaction of the interviewees’ life can be affected by individual characteristics and personal achievement and, at the same time, how the personal aspects can affect the educational level and the working position. It describes this kind of relationships through a multivariate logistic regression model based on the chain graph model. The chapter also studies the relationships under the context-specific independence point of view. It presents the graphical models and the parametrization. ISTAT dataset on the “aspects of everyday life” are also analyzed. In chain regression graph models, variables linked by undirected arcs have a symmetric relationship. Each directed arc links a covariate to its dependent variable. The chapter also presents an application on a real dataset in order to highlight the relationships among a set of variables and identifies the best fitting stratified chain regression graph model.

Nicolussi, F., Cazzaro, M. (2020). Investigation on Life Satisfaction Through (Stratified) Chain Regression Graph Models. In A. Makrides, A. Karagrigoriou, C.h. Skiadas (a cura di), Data Analysis and Applications 3 (pp. 89-99). ISTE WILEY [10.1002/9781119721871.ch5].

Investigation on Life Satisfaction Through (Stratified) Chain Regression Graph Models

Nicolussi, F;Cazzaro, M
2020

Abstract

This chapter studies how the satisfaction of the interviewees’ life can be affected by individual characteristics and personal achievement and, at the same time, how the personal aspects can affect the educational level and the working position. It describes this kind of relationships through a multivariate logistic regression model based on the chain graph model. The chapter also studies the relationships under the context-specific independence point of view. It presents the graphical models and the parametrization. ISTAT dataset on the “aspects of everyday life” are also analyzed. In chain regression graph models, variables linked by undirected arcs have a symmetric relationship. Each directed arc links a covariate to its dependent variable. The chapter also presents an application on a real dataset in order to highlight the relationships among a set of variables and identifies the best fitting stratified chain regression graph model.
Capitolo o saggio
Chain Regression Model, Multivariate Regression Model, Context-specific independence
English
Data Analysis and Applications 3
9781786305343
Nicolussi, F., Cazzaro, M. (2020). Investigation on Life Satisfaction Through (Stratified) Chain Regression Graph Models. In A. Makrides, A. Karagrigoriou, C.h. Skiadas (a cura di), Data Analysis and Applications 3 (pp. 89-99). ISTE WILEY [10.1002/9781119721871.ch5].
Nicolussi, F; Cazzaro, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/270652
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