This paper presents a data driven approach that enables one to obtain a global measure of imbalance and to test it in a multivariate way. The main idea is based on the general framework of Partial Dependence Analysis ([2]), and thus of Conditional Multiple Correspondences Analysis ([4]) as tools for investigating the dependence relationship between a set of observable categorical covariates ( X ) and an assignment-to-treatment indicator variable (T), in order to obtain a global measure of imbalance according to their dependence structure.

Camillo, F., D'Attoma, I. (2009). A Multivariate Approach to Assess Balance of Categorical Covariates in Observational Studies. Padova : CLEUP.

A Multivariate Approach to Assess Balance of Categorical Covariates in Observational Studies

D'ATTOMA, IDA
2009

Abstract

This paper presents a data driven approach that enables one to obtain a global measure of imbalance and to test it in a multivariate way. The main idea is based on the general framework of Partial Dependence Analysis ([2]), and thus of Conditional Multiple Correspondences Analysis ([4]) as tools for investigating the dependence relationship between a set of observable categorical covariates ( X ) and an assignment-to-treatment indicator variable (T), in order to obtain a global measure of imbalance according to their dependence structure.
2009
Book of short papers, Seventh Scientific Meeting of the CLAssification and Data Analysis Group of the Italian Statistical Society
35
38
Camillo, F., D'Attoma, I. (2009). A Multivariate Approach to Assess Balance of Categorical Covariates in Observational Studies. Padova : CLEUP.
Camillo, Furio; D'Attoma, Ida
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/568412
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