Weighted Likelihood for Semiparametric Models and Two‐phase Stratified Samples, with Application to Cox Regression
From MaRDI portal
Publication:5430599
DOI10.1111/j.1467-9469.2006.00523.xzbMath1142.62014arXivmath/0511389OpenAlexW2007180951MaRDI QIDQ5430599
Jon A. Wellner, Norman E. Breslow
Publication date: 16 December 2007
Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/math/0511389
Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Sampling theory, sample surveys (62D05) Estimation in survival analysis and censored data (62N02)
Related Items
Nutritional epidemiology methods and related statistical challenges and opportunities, Z-estimation and stratified samples: application to survival models, More efficient estimators for marginal additive hazards model in case-cohort studies with multiple outcomes, Analysis of two-phase sampling data with semiparametric additive hazards models, Comparing Biomarkers as Principal Surrogate Endpoints, Asymptotic theory for the semiparametric accelerated failure time model with missing data, Efficient and Robust Methods for Causally Interpretable Meta-Analysis: Transporting Inferences from Multiple Randomized Trials to a Target Population, Weighted analyses for cohort sampling designs, Bayesian estimation under informative sampling, Connections between Survey Calibration Estimators and Semiparametric Models for Incomplete Data, Buckley-James Type Estimator for Censored Data with Covariates Missing by Design, A General Statistical Framework for Multistage Designs, Variance Estimation under Two‐Phase Sampling, Case‐base methods for studying vaccination safety, Recent progresses in outcome-dependent sampling with failure time data, Complex sampling designs: uniform limit theorems and applications, Nested exposure case-control sampling: a sampling scheme to analyze rare time-dependent exposures, Multiplicative rates model for recurrent events in case-cohort studies, Norman Edward Breslow–Key figure in the foundation of modern biostatistics, Improving Efficiency of Parameter Estimation in Case-Cohort Studies with Multivariate Failure Time Data, Uncertainty Estimation for Pseudo‐Bayesian Inference Under Complex Sampling, Model-Robust Inference for Clinical Trials that Improve Precision by Stratified Randomization and Covariate Adjustment, A quadratic upper bound algorithm for regression analysis of credit risk under the proportional hazards model with case-cohort data, Secondary analysis under cohort sampling designs using conditional likelihood, On the Breslow estimator, Weighted likelihood estimation under two-phase sampling, Pseudo-likelihood for case–cohort studies under length-biased sampling, A class of weighted estimators for additive hazards model in case-cohort studies, Weighted Likelihood Method for Grouped Survival Data in Case–Cohort Studies with Application to HIV Vaccine Trials, Resampling Procedures for Making Inference Under Nested Case–Control Studies, Nonparametric inference for distribution functions with stratified samples, Semiparametric inference for merged data from multiple data sources, Evaluating the Predictive Value of Biomarkers with Stratified Case‐Cohort Design, Bayesian pairwise estimation under dependent informative sampling, Additive-multiplicative hazards model for case-cohort studies with multiple disease outcomes, A Unified Approach to Semiparametric Transformation Models Under General Biased Sampling Schemes, Regression Calibration in Semiparametric Accelerated Failure Time Models, Kernel machine testing for risk prediction with stratified case cohort studies, Using the whole cohort in the analysis of countermatched samples, Outcome-dependent sampling with interval-censored failure time data, 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’, Asymptotic results for fitting marginal hazard models from stratified case-cohort studies with multiple disease outcomes, Semiparametric estimation for the non-mixture cure model in case-cohort and nested case-control studies, Nonparametric Maximum Likelihood Estimators of Time-Dependent Accuracy Measures for Survival Outcome Under Two-Stage Sampling Designs, Bayesian estimation under informative sampling with unattenuated dependence, Marginal Hazards Regression for Retrospective Studies within Cohort with Possibly Correlated Failure Time Data, Multiplier \(U\)-processes: sharp bounds and applications, Conditional screening for ultrahigh-dimensional survival data in case-cohort studies, Relative risk regression for current status data in case-cohort studies
Cites Work
- Unnamed Item
- Large sample theory for semiparametric regression models with two-phase, outcome dependent sampling.
- Exposure stratified case-cohort designs
- Modeling survival data: extending the Cox model
- Information bounds for Cox regression models with missing data.
- Weak convergence and empirical processes. With applications to statistics
- Generalized Case–cohort Sampling
- A paradox concerning nuisance parameters and projected estimating functions
- The Estimation of Choice Probabilities from Choice Based Samples
- Semiparametric Methods for Response-Selective and Missing Data Problems in Regression
- Estimation of Regression Coefficients When Some Regressors Are Not Always Observed
- Fitting regression models to case-control data by maximum likelihood
- On the Robustness of Weighted Methods for Fitting Models to Case–Control Edata
- Maximum Likelihood Estimation for Cox's Regression Model Under Case-Cohort Sampling
- On fitting Cox's proportional hazards models to survey data
- Additive hazards regression for case-cohort studies
- Improving the Efficiency of Relative-Risk Estimation in Case-Cohort Studies
- Contribution to the Theory of Sampling Human Populations
- A Generalization of Sampling Without Replacement From a Finite Universe