A study of regression calibration in a partially observed stratified Cox model

DOI10.1016/j.jspi.2008.04.024zbMath1149.62080OpenAlexW1992207748MaRDI QIDQ958788

Eve Leconte, Jean-François Dupuy

Publication date: 8 December 2008

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2008.04.024

zbMATH Keywords

stratified Cox modelcensored dataregression calibrationmissing stratum indicators

Mathematics Subject Classification ID

Related Items (5)

A goodness-of-fit test for the stratified proportional hazards model for survival data ⋮ Unnamed Item ⋮ Maximum likelihood estimation in a partially observed stratified regression model with censored data ⋮ Censored count data regression with missing censoring information ⋮ On the random effects Cox model with time-varying regression parameter

Uses Software

• Stata
• timereg
• BLINPLUS
• Multsurr
• relibpls8

Cites Work

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• Cox's regression model for counting processes: A large sample study
• Regression calibration for logistic regression with multiple surrogates for one exposure
• Survival analysis. Techniques for censored and truncated data
• A comparison of regression calibration approaches for designs with internal validation data
• Robust sandwich covariance estimation for regression calibration estimator in Cox regression with measurement error.
• Equivalence of regression calibration methods in main study/external validation study designs
• Dynamic regression models for survival data.
• Covariate measurement errors and parameter estimation in a failure time regression model
• Inference and missing data
• Regression Calibration in Failure Time Regression
• Bias reduction of maximum likelihood estimates
• Estimation in the Cox Model with Missing Covariate Data
• Modeling the Relationship of Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4 Counts in Patients with AIDS
• Statistical models based on counting processes

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