Using information criteria to select the correct variance-covariance structure for longitudinal data in ecology

Barnett, Adrian G., Koper, Nicola, Dobson, Annette J., Schmiegelow, Fiona and Manseau, Micheline (2010) Using information criteria to select the correct variance-covariance structure for longitudinal data in ecology. Methods in Ecology and Evolution, 1 1: 15-24. doi:10.1111/j.2041-210X.2009.00009.x

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Author Barnett, Adrian G.
Koper, Nicola
Dobson, Annette J.
Schmiegelow, Fiona
Manseau, Micheline
Title Using information criteria to select the correct variance-covariance structure for longitudinal data in ecology
Journal name Methods in Ecology and Evolution   Check publisher's open access policy
ISSN 2041-210X
Publication date 2010-03
Year available 2010
Sub-type Article (original research)
DOI 10.1111/j.2041-210X.2009.00009.x
Volume 1
Issue 1
Start page 15
End page 24
Total pages 10
Editor Rob Freckleton
Elizabeth Horne
Place of publication London, U.K.
Publisher British Ecological Society
Collection year 2011
Language eng
Formatted abstract
1. Ecological data sets often use clustered measurements or use repeated sampling in a longitudinal design. Choosing the correct covariance structure is an important step in the analysis of such data, as the covariance describes the degree of similarity among the repeated observations.

2. Three methods for choosing the covariance are: the Akaike information criterion (AIC), the quasi-information criterion (QIC) and the deviance information criterion (DIC). We compared the methods using a simulation study and using a data set that explored effects of forest fragmentation on avian species richness over 15 years.

3.
The overall success was 80·6% for the AIC, 29·4% for the QIC and 81·6% for the DIC. For the forest fragmentation study the AIC and DIC selected the unstructured covariance, whereas the QIC selected the simpler autoregressive covariance. Graphical diagnostics suggested that the unstructured covariance was probably correct.

4. We recommend using DIC for selecting the correct covariance structure.
© 2010 The Authors. Journal compilation © 2010 British Ecological Society
Keyword Bayesian methods
Correlated data
Covariance structure
Information criteria
Generalized estimating equation
Longitudinal data
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2011 Collection
School of Public Health Publications
 
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Created: Wed, 09 Mar 2011, 15:53:38 EST by Geraldine Fitzgerald on behalf of School of Public Health