Double‐Robust Semiparametric Estimator for Differences in Restricted Mean Lifetimes in Observational Studies

DOI10.1111/j.1541-0420.2012.01759.xzbMath1258.62117OpenAlexW2006873011WikidataQ36205270 ScholiaQ36205270MaRDI QIDQ4911920

Douglas E. Schaubel, Min Zhang

Publication date: 20 March 2013

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3432755

zbMATH Keywords

Cox regressionaverage causal effectinverse weightingcumulative treatment effectdouble robust estimator

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Censored data models (62N01)

Related Items (11)

Estimating restricted mean treatment effects with additive-multiplicative hazards models ⋮ Estimating the average treatment effect on survival based on observational data and using partly conditional modeling ⋮ Discussion of “A Risk-Based Measure of Time-Varying Prognostic Discrimination for Survival Models,” by C. Jason Liang and Patrick J. Heagerty ⋮ Making apples from oranges: Comparing noncollapsible effect estimators and their standard errors after adjustment for different covariate sets ⋮ Propensity Score Weighting Analysis of Survival Outcomes Using Pseudo-Observations ⋮ Nonparametric and semiparametric estimators of restricted mean survival time under length-biased sampling ⋮ Adjusted log-rank test with double inverse weighting under dependent censoring ⋮ Semiparametric methods to contrast gap time survival functions: Application to repeat kidney transplantation ⋮ Two-sample tests for survival data from observational studies ⋮ Semiparametric inference of treatment effects on restricted mean survival time in two sample problems from length-biased samples ⋮ Landmark estimation of survival and treatment effects in observational studies

Cites Work

• Unnamed Item
• Doubly Robust Estimation in Missing Data and Causal Inference Models
• Ignorability and coarse data
• Bayesian inference for causal effects: The role of randomization
• Unified methods for censored longitudinal data and causality
• Robust inference for univariate proportional hazards frailty regression models
• Causal Inference on the Difference of the Restricted Mean Lifetime Between Two Groups
• Estimating Differences in Restricted Mean Lifetime Using Observational Data Subject to Dependent Censoring
• The Robust Inference for the Cox Proportional Hazards Model
• Adjustment for Missingness Using Auxiliary Information in Semiparametric Regression
• Misspecified proportional hazard models
• Restricted Mean Life With Adjustment for Covariates
• Partial likelihood
• Restricted Mean Life with Covariates: Modification and Extension of a Useful Survival Analysis Method
• Estimation of Regression Coefficients When Some Regressors Are Not Always Observed
• Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models

This page was built for publication: Double‐Robust Semiparametric Estimator for Differences in Restricted Mean Lifetimes in Observational Studies