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