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The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

The statistical analysis of mitochondrial DNA polymorphisms: chi 2 and the problem of small samples.

Open access
·1989·Molecular Biology and Evolution

Abstract

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.

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Crossref · 10.1093/oxfordjournals.molbev.a040568

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Metadata

Venue
Molecular Biology and Evolution
Published
1989-09
Volume
6
Issue
5
Pages
539-45
ISSN
  • 0737-4038 (ISSN-L)
  • 1537-1719
OpenAlex
W2109678076
Cited by
867
References
5
FWCI
4.19
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: The statistical analysis of mitochondrial DNA polymorphisms: chi 2 and the problem of small samples. https://app.cochat.ai/papers/10.1093/oxfordjournals.molbev.a040568
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The statistical analysis of mitochondrial DNA polymorphisms: chi 2 and the problem of small samples. (1989). Molecular Biology and Evolution. https://doi.org/10.1093/oxfordjournals.molbev.a040568

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.