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.
Titolo: | A note on the use of recursive partitioning in causal inference | |
Autori: | ||
Data di pubblicazione: | 2015 | |
Handle: | http://hdl.handle.net/11584/123821 | |
ISBN: | 9783319173764 | |
Tipologia: | 2.1 Contributo in volume (Capitolo o Saggio) |
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