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A Bayesian proportional hazards regression model with non-ignorably missing time-varying covariates

Missing covariate data is common in observational studies of time to an event, especially when covariates are repeatedly measured over time. Failure to account for the missing data can lead to bias or loss of efficiency, especially when the data are non-ignorably missing. Previous work has focused o...

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Main Authors: Bradshaw, Patrick T., Ibrahim, Joseph G., Gammon, Marilie D.
格式: Artigo
語言:Inglês
出版: 2010
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在線閱讀:https://ncbi.nlm.nih.gov/pmc/articles/PMC3253577/
https://ncbi.nlm.nih.gov/pubmed/20960582
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.4076
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