Propensity score model specification for estimation of average treatment effects

DOI10.1016/j.jspi.2010.01.033zbMath1184.62173OpenAlexW2073761350MaRDI QIDQ963888

Ingeborg Waernbaum

Publication date: 14 April 2010

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2010.01.033

zbMATH Keywords

matchingobservational studiescausal effectpropensity score

Mathematics Subject Classification ID

Estimation in survival analysis and censored data (62N02)

Related Items (3)

Effects of correlated covariates on the asymptotic efficiency of matching and inverse probability weighting estimators for causal inference ⋮ Supervised clustering of label ranking data using label preference information ⋮ Targeted smoothing parameter selection for estimating average causal effects

Cites Work

• Functional decomposition of polynomials: the tame case
• Bayesian inference for causal effects: The role of randomization
• Multivariate polynomial decomposition
• Sufficient Conditions for the Consistency of Maximum Likelihood Estimation Despite Misspecification of Distribution in Multinomial Discrete Choice Models
• The central role of the propensity score in observational studies for causal effects
• Matching As An Econometric Evaluation Estimator
• On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects
• Identification of Binary Response Models
• Large Sample Properties of Matching Estimators for Average Treatment Effects
• Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score

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