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BiMM tree: A decision tree method for modeling clustered and longitudinal binary outcomes
Clustered binary outcomes are frequently encountered in clinical research (e.g. longitudinal studies). Generalized linear mixed models (GLMMs) for clustered endpoints have challenges for some scenarios (e.g. data with multi-way interactions and nonlinear predictors unknown a priori). We develop an a...
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| Publicat a: | Commun Stat Simul Comput |
|---|---|
| Autors principals: | , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2018
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7202553/ https://ncbi.nlm.nih.gov/pubmed/32377032 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/03610918.2018.1490429 |
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