Cargando…
Bayesian analysis for partly linear Cox model with measurement error and time‐varying covariate effect
The Cox proportional hazards model is commonly used to estimate the association between time‐to‐event and covariates. Under the proportional hazards assumption, covariate effects are assumed to be constant in the follow‐up period of study. When measurement error presents, common estimation methods t...
Autores principales: | Pan, Anqi, Song, Xiao, Huang, Hanwen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9489624/ https://www.ncbi.nlm.nih.gov/pubmed/35899596 http://dx.doi.org/10.1002/sim.9531 |
Ejemplares similares
-
Bayesian imputation of time-varying covariates in linear mixed
models
por: Erler, Nicole S, et al.
Publicado: (2017) -
Cox models with time‐varying covariates and partly‐interval censoring–A maximum penalised likelihood approach
por: Webb, Annabel, et al.
Publicado: (2022) -
Analysis of the Cox Model with Longitudinal Covariates with Measurement Errors and Partly Interval Censored Failure Times, with Application to an AIDS Clinical Trial
por: Sun, Yanqing, et al.
Publicado: (2023) -
Multiple imputation in Cox regression when there are time‐varying effects of covariates
por: Keogh, Ruth H., et al.
Publicado: (2018) -
Generating survival times to simulate Cox proportional hazards models with time-varying covariates
por: Austin, Peter C
Publicado: (2012)