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An additive Gaussian process regression model for interpretable non-parametric analysis of longitudinal data
Biomedical research typically involves longitudinal study designs where samples from individuals are measured repeatedly over time and the goal is to identify risk factors (covariates) that are associated with an outcome value. General linear mixed effect models are the standard workhorse for statis...
Autores principales: | Cheng, Lu, Ramchandran, Siddharth, Vatanen, Tommi, Lietzén, Niina, Lahesmaa, Riitta, Vehtari, Aki, Lähdesmäki, Harri |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470127/ https://www.ncbi.nlm.nih.gov/pubmed/30996266 http://dx.doi.org/10.1038/s41467-019-09785-8 |
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