title: Statistical analysis of data in support of the Barker hypothesis, advantages of using random effects regression model in hierarchical data.
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.
authors.affiliation: MRC Environmental Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton SO16 6YD, UK.
authors.forename: C
authors.initials: C
authors.lastname: Osmond
authors.forename: W Y
authors.initials: WY
authors.lastname: Kwong
authors.forename: T P
authors.initials: TP
authors.lastname: Fleming
mesh_terms: D000704:Analysis of Variance; D000818:Animals; D001794:Blood Pressure / Q000502:physiology; D003627:Data Interpretation, Statistical; D015233:Models, Statistical; D011897:Random Allocation; D051381:Rats / Q000502:physiology*; D012044:Regression Analysis; D012107:Research Design