Asymptotic distribution theory on pseudo semiparametric maximum likelihood estimator with covariates missing not at random
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Publication:5079995
DOI10.1080/03610926.2019.1678639OpenAlexW2981989051MaRDI QIDQ5079995
Ling Hui Jin, Lisha Guo, Yan Yan Liu
Publication date: 30 May 2022
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2019.1678639
consistencyasymptotic normalitymissing not at randompseudo semiparametric maximum likelihood estimation
Asymptotic properties of nonparametric inference (62G20) Censored data models (62N01) Statistics (62-XX) Estimation in survival analysis and censored data (62N02)
Cites Work
- Unnamed Item
- Maximum likelihood inference for the Cox regression model with applications to missing covariates
- Maximum likelihood estimation in the proportional hazards cure model
- Weak convergence and empirical processes. With applications to statistics
- Posterior propriety and computation for the Cox regression model with applications to missing covariates
- Cox Regression with Incomplete Covariate Measurements
- On using the Cox proportional hazards model with missing covariates
- Double-Semiparametric Method for Missing Covariates in Cox Regression Models
- Proportional Hazards Regression with Missing Covariates
- Estimation under Cox proportional hazards model with covariates missing not at random
- Estimation in a Cox Proportional Hazards Cure Model
- Likelihood-Based Methods for Missing Covariates in the Cox Proportional Hazards Model
- Auxiliary covariate data in failure time regression
- Weighted Estimators for Proportional Hazards Regression With Missing Covariates
- Maximum Likelihood Estimation of Misspecified Models