Evaluating inverse propensity score weighting in the presence of many treatments. An application to the estimation of the neighbourhood effect

DOI10.1080/00949655.2020.1832092OpenAlexW3120162878MaRDI QIDQ5065257

Unnamed Author, Bruno Arpino, Unnamed Author

Publication date: 18 March 2022

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: http://paduaresearch.cab.unipd.it/12911/1/working_paper_5_SilanArpinoBoccuzzo-1.pdf

zbMATH Keywords

inverse probability of treatment weightingneighbourhood effectgeneralized boosted modelmulti-treatment

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Identification of neighborhood clusters on data balanced by a poset-based approach

Uses Software

• twang

Cites Work

• Estimation of causal effects with multiple treatments: a review and new ideas
• Model-Based Direct Adjustment
• The role of the propensity score in estimating dose-response functions
• Comparison of various machine learning algorithms for estimating generalized propensity score
• A comparison of machine learning algorithms and covariate balance measures for propensity score matching and weighting
• Causal inference for average treatment effects of multiple treatments with non-normally distributed outcome variables
• Causal Inference for Statistics, Social, and Biomedical Sciences

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