The DOI matches its Crossref record.
Permutation Tests for Association Between Two Distance Matrices
Abstract
—Systematists and geneticists often wish to compare two pair-wise distance or similarity matrices based on different characters. Conventional correlation tests are not appropriate in such situations because of dependencies among the entries in each matrix. A broad class of permutation tests for association between distance matrices is described. Specific members of the class are discussed and compared using real and simulated data. Statistics resembling Kendall's tau and Spearman's rho are found to have desirable power and invariance properties.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
PROTEST: A PROcrustean Randomization TEST of community environment concordance
Jackson, D. A. (1995) · Écoscience · doi:10.1080/11956860.1995.11682297 · Cited by 478
Spatial Analysis Of Genetic Variation In Plant Populations
Heywood, J. (1991) · Annual Review of Ecology and Systematics · doi:10.1146/annurev.ecolsys.22.1.335 · Cited by 448
WALKER, J. (1997) · Biological Journal of the Linnean Society · doi:10.1006/bijl.1996.9999 · Cited by 401
SCHEL, A. M., RAWLINGS, B., CLAIDIÈRE, N., WILKE, C., WATHAN, J., RICHARDSON, J., PEARSON, S., S. HERRELKO, E., WHITEN, A., & SLOCOMBE, K. (2013) · American Journal of Primatology · doi:10.1002/ajp.22101 · Cited by 65
Metadata
- Authors
- Dietz, E. J.
- Venue
- Systematic Biology
- Publisher
- Oxford University Press (OUP)
- Published
- 1983-03-01
- Volume
- 32
- Issue
- 1
- Pages
- 21-26
- ISSN
- 1063-5157 (ISSN-L)
- 1076-836X
- OpenAlex
- W2320668971
- Cited by
- 259
- References
- 0
- FWCI
- 3.79
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Permutation Tests for Association Between Two Distance Matrices. https://app.cochat.ai/papers/10.1093/sysbio/32.1.21
- The paper
- Dietz, E. J. (1983). Permutation Tests for Association Between Two Distance Matrices. Systematic Biology. https://doi.org/10.1093/sysbio/32.1.21
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
