Wu Chih-Chieh, Grimson Roger C, Shete Sanjay
Department of Epidemiology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas 77030.
Clinical Statistics Consulting, Stony Brook, New York 11790.
Commun Stat Simul Comput. 2010;39(3):612-623. doi: 10.1080/03610910903528335.
Sophisticated statistical analyses of incidence frequencies are often required for various epidemiologic and biomedical applications. Among the most commonly applied methods is Pearson's test, which is structured to detect non-specific anomalous patterns of frequencies and is useful for testing the significance for incidence heterogeneity. However, the Pearson's test 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's test. We elucidated and illustrated the differences in sensitivity among our tests and the Pearson's test 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.
各种流行病学和生物医学应用通常需要对发病率进行复杂的统计分析。最常用的方法之一是Pearson检验，其旨在检测频率的非特异性异常模式，可用于检验发病率异质性的显著性。然而，Pearson检验在评估特定单元格（或类别）中频率的显著性是否仅由偶然因素导致时效率不高。我们最近基于最大和最小频率开发了用于检测疾病病例时间异常的统计检验；这些检验实际上是为检验特定高频率或低频率的显著性而设计的。我们表明，与Pearson检验相比，我们提出的方法在检验极端单元格计数时更敏感、更有效。通过分析一组朗格汉斯细胞组织细胞增多症病例数据集及其假设集，我们阐明并说明了我们的检验与Pearson检验在敏感性上的差异。我们还使用各种单元格数量集和替代频率计算并比较了这些方法的统计功效。我们的研究将为研究人员提供有用的指导方针，以便为他们的研究选择合适的检验方法。
