Estimating survival treatment effects with covariate adjustment using propensity score

DOI10.1007/s10114-022-0508-9zbMath1503.62085OpenAlexW4283325488MaRDI QIDQ2106861

Xin Cheng Zhang, Yong-Xiu Cao, Ji-Chang Yu

Publication date: 29 November 2022

Published in: Acta Mathematica Sinica. English Series (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10114-022-0508-9

zbMATH Keywords

accelerated failure time modelpropensity scoreobservational studycovariate adjustmentsimultaneous estimating equations

Mathematics Subject Classification ID

Censored data models (62N01) Estimation in survival analysis and censored data (62N02) Reliability and life testing (62N05) Causal inference from observational studies (62D20)

Cites Work

• Unnamed Item
• Cox's regression model for counting processes: A large sample study
• Accelerated failure time model for data from outcome-dependent sampling
• Estimating regression parameters using linear rank tests for censored data
• Rank regression methods for left-truncated and right-censored data
• A large sample study of rank estimation for censored regression data
• Induced smoothing for the semiparametric accelerated failure time model: asymptotics and extensions to clustered data
• The central role of the propensity score in observational studies for causal effects
• Covariate adjustment via propensity scores for recurrent events in the presence of dependent censoring
• Inference for proportional hazard model with propensity score
• Causal Inference for Statistics, Social, and Biomedical Sciences

This page was built for publication: Estimating survival treatment effects with covariate adjustment using propensity score