Mitigating bias from intermittent measurement of time-dependent covariates in failure time analysis
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Publication:6627384
DOI10.1002/sim.8517zbMATH Open1546.6236MaRDI QIDQ6627384
Shu Jiang, Richard J. Cook, Leilei Zeng
Publication date: 29 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- Cox's regression model for counting processes: A large sample study
- Joint Models for Longitudinal and Time-to-Event Data
- Joint Analysis of Longitudinal Data Comprising Repeated Measures and Times to Events
- The Robust Inference for the Cox Proportional Hazards Model
- Measurement Error
- Misspecified proportional hazard models
- An Additive–Multiplicative Cox–Aalen Regression Model
- Multistate Models for the Analysis of Life History Data
- Modeling the Relationship of Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4 Counts in Patients with AIDS
- Modelling Progression of CD4-Lymphocyte Count and Its Relationship to Survival Time
- Measurement Error in Nonlinear Models
- Attenuation caused by infrequently updated covariates in survival analysis
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