Consequences of ignoring clustering in linear regression

Consequences of ignoring clustering in linear regression

Abstract Background Clustering of observations is a common phenomenon in epidemiological and clinical research. Previous studies have highlighted the importance of using multilevel analysis to account for such clustering, but in practice, methods ignoring clustering are often employed. We used simul...

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Bibliographic Details
Main Authors: Georgia Ntani, Hazel Inskip, Clive Osmond, David Coggon
Format: Article
Language:English
Published: BMC 2021-07-01
Series:BMC Medical Research Methodology
Subjects:
Clustering
Linear regression
Random intercept model
Consequences
Simulation
Comparison
Online Access:https://doi.org/10.1186/s12874-021-01333-7

Internet

https://doi.org/10.1186/s12874-021-01333-7

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