Journal article
MODELING TEMPORAL GRADIENTS IN REGIONALLY AGGREGATED CALIFORNIA ASTHMA HOSPITALIZATION DATA
The annals of applied statistics, v 7(1), pp 154-176
01 Mar 2013
PMID: 29606992
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Advances in Geographical Information Systems (GIS) have led to the enormous recent burgeoning of spatial-temporal databases and associated statistical modeling. Here we depart from the rather rich literature in space-time modeling by considering the setting where space is discrete (e. g., aggregated data over regions), but time is continuous. Our major objective in this application is to carry out inference on gradients of a temporal process in our data set of monthly county level asthma hospitalization rates in the state of California, while at the same time accounting for spatial similarities of the temporal process across neighboring counties. Use of continuous time models here allows inference at a finer resolution than at which the data are sampled. Rather than use parametric forms to model time, we opt for a more flexible stochastic process embedded within a dynamic Markov random field framework. Through the matrix-valued covariance function we can ensure that the temporal process realizations are mean square differentiable, and may thus carry out inference on temporal gradients in a posterior predictive fashion. We use this approach to evaluate temporal gradients where we are concerned with temporal changes in the residual and fitted rate curves after accounting for seasonality, spatiotemporal ozone levels and several spatially-resolved important sociodemographic covariates.
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Details
- Title
- MODELING TEMPORAL GRADIENTS IN REGIONALLY AGGREGATED CALIFORNIA ASTHMA HOSPITALIZATION DATA
- Creators
- Harrison Quick - University of MinnesotaSudipto Banerjee - University of MinnesotaBradley P. Carlin - University of Minnesota
- Publication Details
- The annals of applied statistics, v 7(1), pp 154-176
- Publisher
- Inst Mathematical Statistics
- Number of pages
- 23
- Grant note
- RC1GM092400 / NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of General Medical Sciences (NIGMS) R01 CA112444 / NCI NIH HHS; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI) R01CA112444 / NATIONAL CANCER INSTITUTE; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI) RC1 GM092400 / NIGMS NIH HHS; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of General Medical Sciences (NIGMS)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Epidemiology and Biostatistics
- Web of Science ID
- WOS:000322828900007
- Scopus ID
- 2-s2.0-84876059738
- Other Identifier
- 991020099923504721
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- Web of Science research areas
- Statistics & Probability