Title of article :
Structural equation models for area health outcomes with model selection
Author/Authors :
Peter Congdon، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2011
Abstract :
Recent analyses seeking to explain variation in area health outcomes often consider the impact on them of
latent measures (i.e. unobserved constructs) of population health risk. The latter are typically obtained by
forms of multivariate analysis, with a small set of latent constructs derived from a collection of observed
indicators, and a few recent area studies take such constructs to be spatially structured rather than independent
over areas. A confirmatory approach is often applicable to the model linking indicators to constructs,
based on substantive knowledge of relevant risks for particular diseases or outcomes. In this paper, population
constructs relevant to a particular set of health outcomes are derived using an integrated model
containing all the manifest variables, namely health outcome variables, as well as indicator variables
underlying the latent constructs. A further feature of the approach is the use of variable selection techniques
to select significant loadings and factors (especially in terms of effects of constructs on health
outcomes), so ensuring parsimonious models are selected. A case study considers suicide mortality and
self-harm contrasts in the East of England in relation to three latent constructs: deprivation, fragmentation
and urbanicity.
Keywords :
Spatial , Small area , Structural equation model , Model selection , Bayesian , SUICIDE , latent constructs
Journal title :
JOURNAL OF APPLIED STATISTICS
Journal title :
JOURNAL OF APPLIED STATISTICS