Summary
The data basis for finding temporal or spatial disease clusters in epidemiologic investigations is quite often a large one, and, in this case, the usage of exact statistical tests is not feasible. However, sometimes only small samples of patients are available and it becomes possible to apply exact statistical methods. Grimson et al. (1992, 1993) derived combinatorial tests for different kinds of null hypotheses and test statistics. In general, these tests are only feasible for very small sample sizes. For some situations, we derive exact bounds for the p-values of combinatorial tests for clustering which allow the application of these tests not only for small, but also for medium and large sample sizes.
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© 1996 Springer-Verlag Berlin · Heidelberg
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Krauth, J. (1996). Bounds for p-values of Combinatorial Tests for Clustering in Epidemiology. In: Bock, HH., Polasek, W. (eds) Data Analysis and Information Systems. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-80098-6_6
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DOI: https://doi.org/10.1007/978-3-642-80098-6_6
Publisher Name: Springer, Berlin, Heidelberg
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