Non-Ignorable Missing Covariate Data in Survival Analysis: A Case-Study of an International Breast Cancer Study Group Trial

DOI10.1046/j.1467-9876.2003.05168.xzbMath1111.62344OpenAlexW2072058232MaRDI QIDQ3435809

Joseph G. Ibrahim, Amy H. Herring, Stuart R. Lipsitz

Publication date: 7 May 2007

Published in: Journal of the Royal Statistical Society Series C: Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1046/j.1467-9876.2003.05168.x

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)

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A calibrated Bayesian method for the stratified proportional hazards model with missing covariates, Maximum likelihood inference for the Cox regression model with applications to missing covariates, Imputing missing quality of life data as covariate in survival analysis of the International Breast Cancer Study Group Trials VI and VII, Missing data methods in longitudinal studies: a review, Alternative expectation approaches for expectation-maximization missing data imputations in cox regression, An index of local sensitivity to non-ignorability for parametric survival models with potential non-random missing covariate: an application to the SEER cancer registry data, Stratified Logrank Test of No Randomized Treatment Effect with Missing Stratum Information, Proportional hazards regression in the presence of missing study eligibility information

Cites Work

• Unnamed Item
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• Multiple imputation for the Cox proportional hazards model with missing covariates
• Incomplete Covariates in the Cox Model with Applications to Biological Marker Data
• Latent Class Models for Longitudinal Studies of the Elderly with Data Missing at Random
• Missing Covariates in Generalized Linear Models When the Missing Data Mechanism is Non-ignorable
• A Marginal Model for Analyzing Discrete Outcomes From Longitudinal Surveys With Outcomes Subject to Multiple-Cause Nonresponse
• Likelihood-Based Methods for Missing Covariates in the Cox Proportional Hazards Model
• Cox Regression with Incomplete Covariate Measurements using the EM‐algorithm
• Linear mixed models for longitudinal data
• Bayesian survival analysis