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Joint modeling of longitudinal zero-inflated count and time-to-event data: A Bayesian perspective
Longitudinal zero-inflated count data are encountered frequently in substance-use research when assessing the effects of covariates and risk factors on outcomes. Often, both the time to a terminal event such as death or dropout and repeated measure count responses are collected for each subject. In...
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| Gepubliceerd in: | Stat Methods Med Res |
|---|---|
| Hoofdauteurs: | , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
2016
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5269555/ https://ncbi.nlm.nih.gov/pubmed/27460540 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1177/0962280216659312 |
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