Fitting parametric random effects models in very large data sets with application to VHA national data

BACKGROUND: With the current focus on personalized medicine, patient/subject level inference is often of key interest in translational research. As a result, random effects models (REM) are becoming popular for patient level inference. However, for very large data sets that are characterized by larg...

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Detalles Bibliográficos
Autores principales: Gebregziabher, Mulugeta, Egede, Leonard, Gilbert, Gregory E, Hunt, Kelly, Nietert, Paul J, Mauldin, Patrick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3542162/
https://www.ncbi.nlm.nih.gov/pubmed/23095325
http://dx.doi.org/10.1186/1471-2288-12-163

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3542162/
https://www.ncbi.nlm.nih.gov/pubmed/23095325
http://dx.doi.org/10.1186/1471-2288-12-163

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