Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Comparing hierarchical models for spatio-temporally misaligned data using the deviance information criterion.

L Zhu1, B P Carlin

  • 1Division of Biostatistics, School of Public Health, University of Minnesota, Box 303, Mayo Memorial Building, Minneapolis, Minnesota 55455-0392, USA.

Statistics in Medicine
|August 29, 2000
PubMed
Summary

Bayesian methods effectively smooth disease risk maps, even with spatially misaligned and temporal data. The deviance information criterion (DIC) aids in comparing complex hierarchical models for this data.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Bayesian hierarchical modeling for a non-randomized, longitudinal fall prevention trial with spatially correlated observations.

Statistics in medicine·2011
Same author

Glucagon receptor knockout mice are resistant to diet-induced obesity and streptozotocin-mediated beta cell loss and hyperglycaemia.

Diabetologia·2006
Same author

Anti-inflammatory effects of inhaled nitric oxide are optimized at lower oxygen concentration in experimental Klebsiella pneumoniae pneumonia.

Inflammation research : official journal of the European Histamine Research Society ... [et al.]·2006
Same author

[Isolation by suppression-subtractive hybridization of genes preferentially expressed during early and late fiber development stages in cotton].

Molekuliarnaia biologiia·2006
Same author

Amelogenins in human developing and mature dental pulp.

Journal of dental research·2006
Same author

Risk assessment of organic pesticides pollution in surface water of Hangzhou.

Environmental monitoring and assessment·2006

Area of Science:

  • Biostatistics
  • Spatial Epidemiology
  • Geographic Information Systems

Background:

  • Bayes and empirical Bayes methods are established for smoothing disease risk maps.
  • Spatial misalignment and temporal changes complicate disease risk analysis.
  • Hierarchical Bayesian models are computationally intensive and difficult to compare.

Purpose of the Study:

  • To compare hierarchical Bayesian models for spatially misaligned and temporally evolving areal data.
  • To evaluate the utility of the deviance information criterion (DIC) for model comparison in this context.
  • To investigate the delta method for assessing the significance of DIC differences.

Main Methods:

  • Application of hierarchical Bayesian methods using Markov chain Monte Carlo (MCMC).

Related Experiment Videos

  • Utilized the deviance information criterion (DIC) for model comparison.
  • Employed the delta method to estimate variance for DIC.

    • Main Results:

    • The deviance information criterion (DIC) provides a method for comparing complex hierarchical models.
    • The delta method can be used to assess the statistical significance of differences in DIC.
    • The approach was illustrated using traffic density and paediatric asthma hospitalizations in San Diego County.

    Conclusions:

    • The deviance information criterion (DIC) is a valuable tool for comparing hierarchical Bayesian models with complex data structures.
    • The delta method enhances the interpretability of DIC by providing significance estimates.
    • This methodology is applicable to real-world epidemiological studies with spatial and temporal complexities.