The statistical analysis of mitochondrial DNA polymorphisms: chi 2 and the problem of small samples.
The statistical analysis of mitochondrial DNA polymorphisms: chi 2 and the problem of small samples.
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线粒体DNA多态性统计分析：chi 2与小样本问题。
DOI：
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发表时间：
1989
影响因子：
10.7
通讯作者：
P. Bentzen
中科院分区：
文献类型：
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作者：
D. Roff;P. Bentzen
当样本量很小时，从chi 2偶然性检验获得的显著性水平是可疑的。传统上，这意味着数据必须组合在一起。然而，这种方法可能会模糊异质性，从而潜在地降低统计检验的效力。在本文中，我们提出了一种蒙特卡罗方法来解决这个问题：通过这种方法，不需要对数据进行集总，并且alpha估计的准确性（即1型误差）仅取决于原始数据集的随机化次数。我们用mtDNA研究的数据来说明这种技术，其中经常观察到许多基因型，样本量相对较小。
Significance levels obtained from a chi 2 contingency test are suspect when sample sizes are small. Traditionally this has meant that data must be combined. However, such an approach may obscure heterogeneity and hence potentially reduce the power of the statistical test. In this paper, we present a Monte Carlo solution to this problem: by this method, no lumping of data is required, and the accuracy of the estimate of alpha (i.e., a type 1 error) depends only on the number of randomizations of the original data set. We illustrate this technique with data from mtDNA studies, where numerous genotypes are often observed and sample sizes are relatively small.
果蝇自然群体线粒体DNA多态性的时空异质性。
影响因子：
3.3
作者：
DeSalle,R;Templeton,A;Mori,I;Pletscher,S;Johnston,JS
通讯作者：
Johnston,JS