Empty Cells test

  • temporal
  • global
  • multiple time series
    • Indications/Recommendations for use: When cases cluster the test statistic will be large. Use this test to detect clusters of rare events, so that some of the time periods can reasonably be expected to have 0 cases. For rare events (more).
    Description: A test for time clustering in a single time series or in several time series simultaneously.
    Test statistic: The test statistic, E, is the count of the number of cells with 0 cases. When more than one area (time series) is analyzed an overall Chi square statistic tests for time clustering over all the areas simultaneously.
    The summations are over the number of areas, E is the sum of the number of empty cells, and E(E) and V(E) are the mean and variance of E under the assumption of a random allocation of disease cases among the cells.

    Null Hypothesis: The cases occur at random across the time periods.
    Alternative Hypothesis: Cases cluster in one or more time periods.
    GeoMed Inputs: Counts of cases within consecutive time periods (a time series). The Empty cells test requires the name of a time series (TIM) file.
    GeoMed Outputs:
    • E, E(E), and Var(E)
    • p-value for one-tailed test
    • Plot of E on its expectation E(E) with 45 degree line through origin
    Example Analysis Reference:
    Website maintained by Andy Long. Comments appreciated.
    longa@nku.edu