Sánchez María S, Basten Christopher J, Ferrenberg Alan M, Asmussen Marjorie A, Arnold Jonathan
Department of Genetics, The University of Georgia, Athens, 30602, USA.
Theor Popul Biol. 2006 Mar;69(2):111-20. doi: 10.1016/j.tpb.2005.11.001. Epub 2005 Dec 15.
Many medical and biological studies entail classifying a number of observations according to two factors, where one has two and the other three possible categories. This is the case of, for example, genetic association studies of complex traits with single-nucleotide polymorphisms (SNPs), where the a priori statistical planning, analysis, and interpretation of results are of critical importance. Here, we present methodology to determine the minimum sample size required to detect dependence in 2 x 3 tables based on Fisher's exact test, assuming that neither of the two margins is fixed and only the grand total N is known in advance. We provide the numerical tools necessary to determine these sample sizes for desired power, significance level, and effect size, where only the computational time can be a limitation for extreme parameter values. These programs can be accessed at . This solution of the sample size problem for an exact test will permit experimentalists to plan efficient sampling designs, determine the extent of statistical support for their hypotheses, and gain insight into the repeatability of their results. We apply this solution to the sample size problem to three empirical studies, and discuss the results with specified power and nominal significance levels.
许多医学和生物学研究需要根据两个因素对大量观察结果进行分类，其中一个因素有两种可能的类别，另一个因素有三种可能的类别。例如，在单核苷酸多态性（SNP）与复杂性状的基因关联研究中就是这种情况，其中结果的先验统计规划、分析和解释至关重要。在此，我们提出一种方法，用于确定基于费舍尔精确检验在2×3列联表中检测相关性所需的最小样本量，假设两个边际均不固定且仅预先知道总数N。我们提供了确定所需功效、显著性水平和效应大小的这些样本量所需的数值工具，对于极端参数值而言，唯一的限制可能是计算时间。这些程序可在……获取。精确检验的样本量问题的这种解决方案将使实验人员能够规划高效的抽样设计，确定其假设的统计支持程度，并深入了解其结果的可重复性。我们将此样本量问题的解决方案应用于三项实证研究，并在指定功效和名义显著性水平下讨论结果。
