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

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

<p>Abstract</p> <p>Background</p> <p>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,...

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Bibliographic Details
Main Authors: Gebregziabher Mulugeta, Egede Leonard, Gilbert Gregory E, Hunt Kelly, Nietert Paul J, Mauldin Patrick
Format: Article
Language:English
Published: BMC 2012-10-01
Series:BMC Medical Research Methodology
Subjects:
Generalized linear mixed model
Homogeneity
Random effect meta regression
Longitudinal data
Very large dataset
Online Access:http://www.biomedcentral.com/1471-2288/12/163

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http://www.biomedcentral.com/1471-2288/12/163

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