Selecting and fitting graphical chain models to longitudinal data
Borgoni, Riccardo, Berrington, Ann M. and Smith, Peter W. F. (2004) Selecting and fitting graphical chain models to longitudinal data. Southampton, UK, Southampton Statistical Sciences Research Institute, 33pp. (S3RI Methodology Working Papers, (M04/05) ).
The aim of this paper is to demonstrate how graphical chain models can be used as effective tools in life course research focusing in particular on models for longitudinal prospective data. The substantive research question focuses on whether young motherhood is a pathway through which socio-economic disadvantage in childhood is related to poor self-reported health in adulthood among the 1970 British birth cohort. By breaking down large multivariate systems into simpler more tractable subcomponents and analysing them via local regressions, graphical models helps the understanding of complicated life course processes, show the intermediate relationships between predictors, and aid the understanding of the mechanisms through which potential confounding and mediating factors affect the outcome of interest.
|Item Type:||Monograph (UNSPECIFIED)|
|Subjects:||H Social Sciences > HA Statistics|
|Divisions:||University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
|Date Deposited:||11 Jul 2004|
|Last Modified:||03 Mar 2012 18:06|
|Contributors:||Borgoni, Riccardo (Author)
Berrington, Ann M. (Author)
Smith, Peter W. F. (Author)
|Publisher:||Southampton Statistical Sciences Research Institute|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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