Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
387350 | Expert Systems with Applications | 2010 | 11 Pages |
Abstract
This paper presents a data driven approach that enables one to obtain a measure of comparability between-groups in the presence of observational data.The main idea lies in the use of the general framework of conditional multiple correspondences analysis as a tool 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 comparability between-groups according to their dependence structure. Then, we propose a strategy that enables one to find treatment groups, directly comparable with respect to pre-treatment characteristics, on which estimate local causal effects.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
F. Camillo, Ida D’Attoma,