Z-estimation and stratified samples: application to survival models
From MaRDI portal
Publication:269747
DOI10.1007/s10985-014-9317-5zbMath1333.62237OpenAlexW2092566423WikidataQ35855429 ScholiaQ35855429MaRDI QIDQ269747
Jie Hu, Norman E. Breslow, Jon A. Wellner
Publication date: 6 April 2016
Published in: Lifetime Data Analysis (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc4503541
semiparametric modelsproportional hazardssurvey samplingmodel misspecificationadditive hazardscalibration of sampling weights
Nonparametric estimation (62G05) Censored data models (62N01) Sampling theory, sample surveys (62D05) Estimation in survival analysis and censored data (62N02)
Related Items
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Longitudinal data analysis using generalized linear models
- Cox's regression model for counting processes: A large sample study
- Information and asymptotic efficiency in parametric-nonparametric models
- Survival and event history analysis. A process point of view
- A large sample study of Cox's regression model
- Model assisted survey sampling
- Exposure stratified case-cohort designs
- Modeling survival data: extending the Cox model
- A large sample study of the life table and product limit estimates under random censorship
- Information bounds for Cox regression models with missing data.
- Weak convergence and empirical processes. With applications to statistics
- Weighted likelihood estimation under two-phase sampling
- The Robust Inference for the Cox Proportional Hazards Model
- A Z‐theorem with Estimated Nuisance Parameters and Correction Note for ‘Weighted Likelihood for Semiparametric Models and Two‐phase Stratified Samples, with Application to Cox Regression’
- Non‐parametric Estimation of a Survival Function with Two‐stage Design Studies
- A case-cohort design for epidemiologic cohort studies and disease prevention trials
- Model Robust Confidence Intervals Using Maximum Likelihood Estimators
- Misspecified proportional hazard models
- Calibration Estimators in Survey Sampling
- Asymptotic Statistics
- Semiparametric analysis of the additive risk model
- Estimation of Regression Coefficients When Some Regressors Are Not Always Observed
- A partly parametric additive risk model
- Efficient estimation for case-cohort studies
- Maximum Likelihood Estimation for Cox's Regression Model Under Case-Cohort Sampling
- Efficiency. of infinite dimensional M‐ estimators
- Additive hazards regression for case-cohort studies
- Efficient Estimation of Semiparametric Transformation Models for Two-Phase Cohort Studies
- Connections between Survey Calibration Estimators and Semiparametric Models for Incomplete Data
- Weighted Likelihood for Semiparametric Models and Two‐phase Stratified Samples, with Application to Cox Regression
- Semiparametric models and two-phase samples: Applications to Cox regression
- An Optimum Property of Regular Maximum Likelihood Estimation
- Improving the Efficiency of Relative-Risk Estimation in Case-Cohort Studies