A note on the use of recursive partitioning in causal inference

CONVERSANO, CLAUDIO;CANNAS, MASSIMO;MOLA, FRANCESCO

2015-01-01

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Abstract

A tree-based approach for identification of a balanced group of observations in causal inference studies is presented. The method uses an algorithm based on a multidimensional balance measure criterion applied to the values of the covariates to recursively split the data. Starting from an ad-hoc resampling scheme, observations are finally partitioned in subsets characterized by different degrees of homogeneity, and causal inference is carried out on the most homogeneous subgroups. © Springer International Publishing Switzerland 2015. All rights reserved.