In spatio-temporal disease mapping models, identifiability constraints affect PQL and INLA results
Fecha
2018Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión aceptada / Onetsi den bertsioa
Impacto
|
10.1007/s00477-017-1405-0
Resumen
Disease mapping studies the distribution of relative risks or rates in space and time, and typically relies on
generalized linear mixed models (GLMMs) including fixed
effects and spatial, temporal, and spatio-temporal random
effects. These GLMMs are typically not identifiable and
constraints are required to achieve sensible results. However, automatic specification of constraints can sometime ...
[++]
Disease mapping studies the distribution of relative risks or rates in space and time, and typically relies on
generalized linear mixed models (GLMMs) including fixed
effects and spatial, temporal, and spatio-temporal random
effects. These GLMMs are typically not identifiable and
constraints are required to achieve sensible results. However, automatic specification of constraints can sometimes
lead to misleading results. In particular, the penalized
quasi-likelihood fitting technique automatically centers the
random effects even when this is not necessary. In the
Bayesian approach, the recently-introduced integrated
nested Laplace approximations computing technique can
also produce wrong results if constraints are not wellspecified. In this paper the spatial, temporal, and spatiotemporal interaction random effects are reparameterized
using the spectral decompositions of their precision
matrices to establish the appropriate identifiability constraints. Breast cancer mortality data from Spain is used to
illustrate the ideas. [--]
Materias
Breast cancer,
INLA,
Leroux CAR prior,
PQL,
Space-time interactions
Editor
Springer
Publicado en
Stochastic Environmental Research and Risk Assessment, (2018) 32:749-770
Departamento
Universidad Pública de Navarra/Nafarroako Unibertsitate Publikoa. Institute for Advanced Materials and Mathematics - INAMAT2
Versión del editor
Entidades Financiadoras
This work has been supported by the Spanish
Ministry of Economy and Competitiveness (project MTM2014-
51992-R), and by the Health Department of the Navarre Government
(Project 113, Res.2186/2014).