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Joint Models for Multiple Longitudinal Processes and Time-to-event Outcome
Joint models are statistical tools for estimating the association between time-to-event and longitudinal outcomes. One challenge to the application of joint models is its computational complexity. Common estimation methods for joint models include a two-stage method, Bayesian and maximum-likelihood...
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| Опубликовано в: : | J Stat Comput Simul |
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| Главные авторы: | , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
2016
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5135019/ https://ncbi.nlm.nih.gov/pubmed/27920466 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/00949655.2016.1181760 |
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