Statistical analysis of data in support of the Barker hypothesis, advantages of using random effects regression model in hierarchical data


Osmond, C., Kwong, W.Y. and Fleming, T.P. (2005) Statistical analysis of data in support of the Barker hypothesis, advantages of using random effects regression model in hierarchical data. Reproductive Biomedicine Online, 10, (2), 152-153.

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Description/Abstract

In a recent note by Walters and Edwards (2004), the authors argued that summary statistics should be used in analysing hierarchical data from our earlier analysis of a rat model of developmental programming and the Barker hypothesis (Kwong et al., 2000, 2004). We reiterate here why such a view is inappropriate. Hierarchical data merits multilevel analysis using a 'random effects' model to enable estimation of variances at different levels and easy assessment of other parameters in a complex data structure.

Item Type: Article
Related URLs:
Keywords: barker hypothesis, statistics,
Subjects: R Medicine > R Medicine (General)
H Social Sciences > HA Statistics
Divisions: University Structure - Pre August 2011 > School of Medicine > Developmental Origins of Health and Disease
ePrint ID: 25864
Date Deposited: 12 Apr 2006
Last Modified: 27 Mar 2014 18:14
URI: http://eprints.soton.ac.uk/id/eprint/25864

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