Empirical likelihood calibration estimation for the median treatment difference in observational studies

DOI10.1016/j.csda.2010.09.012zbMath1328.62035OpenAlexW2021555036MaRDI QIDQ901533

Peng Lai, Qi Hua Wang

Publication date: 12 January 2016

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2010.09.012

zbMATH Keywords

calibrationselection biasmissing dataempirical likelihoodcausal inferencemedian treatment effect

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Point estimation (62F10)

Related Items (2)

The specification of the propensity score in multilevel observational studies ⋮ Empirical likelihood based weighted GMM estimation with missing response at random

Uses Software

• Stata
• nnmatch

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Efficient Semiparametric Estimation of Quantile Treatment Effects
• Empirical likelihood for estimating equations with missing values
• Empirical likelihood and general estimating equations
• Empirical likelihood-based inference under imputation for missing response data
• Optimal calibration estimators in survey sampling
• Empirical Likelihood-Based Estimation of the Treatment Effect in a Pretest–Posttest Study
• Partially linear models with missing response variables and error-prone covariates
• Efficient and Doubly Robust Imputation for Covariate-Dependent Missing Responses
• The central role of the propensity score in observational studies for causal effects
• Empirical likelihood-based inference in linear errors-in-covariables models with validation data
• Bahadur representations of the empirical likelihood quantile processes
• On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects
• Empirical-Likelihood-Based Inference in Missing Response Problems and Its Application in Observational Studies
• Empirical Likelihood Inference in Nonlinear Errors-in-Covariables Models With Validation Data
• Measurement Error Models with Auxiliary Data
• A Generalization of Sampling Without Replacement From a Finite Universe

This page was built for publication: Empirical likelihood calibration estimation for the median treatment difference in observational studies