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Related Experiment Videos

Comparing the performance of two indices for spatial model selection: application to two mortality data.

C K Hsiao1, J Y Tzeng, C H Wang

  • 1Divison of Biostatistics, Institute of Epidemiology, National Taiwan University, No. 1, Jen-Ai Rd, Sec. 1, Rm 1542, Taipei 100, Taiwan, R. O.C. ckhsiao@ha.mc.ntu.edu.tw

Statistics in Medicine
|June 27, 2000
PubMed
Summary

This study compares the conditional autoregressive (CAR) model and Poisson gamma model for spatial data analysis. The local to global variability (LG) index suggests the Poisson gamma model is often favored, offering a computationally efficient alternative for identifying high-risk areas.

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Area of Science:

  • Spatial statistics
  • Biostatistics
  • Epidemiology

Background:

  • Analyzing spatially correlated health data is crucial for identifying at-risk populations.
  • Conditional Autoregressive (CAR) models and Poisson gamma models are used to describe spatial autocorrelation.
  • Comparing these models aids in selecting appropriate methods for risk assessment.

Purpose of the Study:

  • To compare the performance of the conditional autoregressive (CAR) model and the Poisson gamma model for spatial data.
  • To evaluate the utility of the local to global variability (LG) index for model selection.
  • To assess model performance using real-world data (Taiwan asthma mortality, Scotland lip cancer) and simulation data.

Main Methods:

  • Utilized the local to global variability (LG) index, a ratio of local to global variability.

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  • Employed the Bayes factor, a Bayesian model selection criterion, for comparison.
  • Estimated LG using posterior modes from BUGS samples and Bayes factor using various approximation methods.

    • Main Results:

    • The LG index values were small for both Taiwan asthma mortality and Scotland lip cancer datasets, favoring the Poisson gamma model.
    • Bayes factor computations were consistent with LG index results.
    • The LG index proved accurate in selecting between Poisson gamma and CAR models.

    Conclusions:

    • The Poisson gamma model may be preferred over the CAR model for the analyzed spatial health data.
    • The LG index is a reliable and computationally efficient tool for selecting between Poisson gamma and CAR models.
    • LG offers a practical first step for model selection in spatial statistical analysis, especially when computational resources are limited.