On the Use of Recursive Partitioning in Causal Inference: A Proposal
CONVERSANO, CLAUDIO;CANNAS, MASSIMO;MOLA, FRANCESCO
2013-01-01
Abstract
A tree-based method for identification of a balanced group of observa- tions in casual inference studies is presented. The method derives from an algorithm which uses a multidimensional balance measure criterion to recursively split the dataset based on the values of the covariates. Observations are finally partitioned in subsets characterized by different degrees of homogeneity. An ad-hoc resampling scheme is used to select the units for which causal inference can be carried out.File | Size | Format | |
---|---|---|---|
Cladag2013_fin.pdf Solo gestori archivio
Description: def
Type: versione editoriale
Size 1.21 MB
Format Adobe PDF
|
1.21 MB | Adobe PDF | & nbsp; View / Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.