title: Exact Statistical Tests for Heterogeneity of Frequencies Based on Extreme Values.
abstract: Sophisticated statistical analyses of incidence frequencies are often required for various epidemiologic and biomedical applications. Among the most commonly applied methods is Pearson'sχ2test, which is structured to detect non-specific anomalous patterns of frequencies and is useful for testing the significance for incidence heterogeneity. However, the Pearson'sχ2test is not efficient for assessing the significance of frequency in a particular cell (or class) to be attributed to chance alone. We recently developed statistical tests for detecting temporal anomalies of disease cases based on maximum and minimum frequencies; these tests are actually designed to test of significance for a particular high or low frequency. We show that our proposed methods are more sensitive and powerful for testing extreme cell counts than is the Pearson'sχ2test. We elucidated and illustrated the differences in sensitivity among our tests and the Pearson'sχ2test by analyzing a data set of Langerhans cell histiocytosis cases and its hypothetical sets. We also computed and compared the statistical power of these methods using various sets of cell numbers and alternative frequencies. Our study will provide investigators with useful guidelines for selecting the appropriate tests for their studies.
authors.affiliation: Department of Epidemiology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas 77030.
authors.forename: Chih-Chieh
authors.initials: CC
authors.lastname: Wu
authors.affiliation: Clinical Statistics Consulting, Stony Brook, New York 11790.
authors.forename: Roger C
authors.initials: RC
authors.lastname: Grimson
authors.affiliation: Department of Epidemiology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas 77030.
authors.forename: Sanjay
authors.initials: S
authors.lastname: Shete
keywords: classical occupancy model; extreme value; maximum; minimum; temporal anomalies