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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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.
|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
|Accepted Date and Publication Date:||
|Date Deposited:||12 Apr 2006|
|Last Modified:||31 Mar 2016 11:48|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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