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Some simple tests for spatial effects around putative sources of health risk

  • Andrew B. Lawson
  • , Fiona L. R. Williams
  • , Yuan Liu

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The need for tests dealing with different features of small area health data is less important with the increase in computation speed of computers and the access to MCMC methods. However there are many situations where exploratory testing could be useful and where MCMC methods are not readily useable or available.

    In this paper, a number of simple tests are derived for the logistic model for case events. This model assumes that a control disease is available and that the events have a binary label relating to case or control state. The tests are derived from likelihood considerations and Monte Carlo critical regions are examined. A simulated evaluation of the tests is presented in terms of Monte Carlo power. A data example is considered.

    Original languageEnglish
    Pages (from-to)493-504
    Number of pages12
    JournalBiometrical Journal
    Volume49
    Issue number4
    DOIs
    Publication statusPublished - Aug 2007

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

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