The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Distance‐based multivariate analyses confound location and dispersion effects
Abstract
Summary: 1. A critical property of count data is its mean–variance relationship, yet this is rarely considered in multivariate analysis in ecology. 2. This study considers what is being implicitly assumed about the mean–variance relationship in distance‐based analyses – multivariate analyses based on a matrix of pairwise distances – and what the effect is of any misspecification of the mean–variance relationship. 3. It is shown that distance‐based analyses make implicit assumptions that are typically out‐of‐step with what is observed in real data, which has major consequences. 4. Potential consequences of this mean–variance misspecification are: confounding location and dispersion effects in ordinations; misleading results when trying to identify taxa in which an effect is expressed; failure to detect a multivariate effect unless it is expressed in high‐variance taxa. 5. Data transformation does not solve the problem. 6. A solution is to use generalised linear models and their recent multivariate generalisations, which is shown here to have desirable properties.
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McCullagh, P., & Nelder, J. A. (1989) · doi:10.1007/978-1-4899-3242-6 · Cited by 16,836
A new method for non-parametric multivariate analysis of variance
Anderson, M. J. (2001) · Austral Ecology · doi:10.1111/j.1442-9993.2001.01070.pp.x · Cited by 13,828
Distance‐Based Tests for Homogeneity of Multivariate Dispersions
Anderson, M. J. (2006) · Biometrics · doi:10.1111/j.1541-0420.2005.00440.x · Cited by 3,304
Aggregation, Variance and the Mean
TAYLOR, L. R. (1961) · Nature · doi:10.1038/189732a0 · Cited by 2,496
Edgington, E., Edgington, E., & Onghena, P. (2007) · doi:10.1201/9781420011814 · Cited by 2,030
Quasi-Poisson vs. negative binomial regression: how should we model overdispersed count data?
Ver Hoef, J. M., & Boveng, P. L. (2007) · Ecology · doi:10.1890/07-0043.1 · Cited by 1,238
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Self-citationReliable, verifiable and efficient monitoring of biodiversity via metabarcoding
Ji, Y., Ashton, L., Pedley, S. M., Edwards, D. P., Tang, Y., Nakamura, A., Kitching, R., Dolman, P. M., Woodcock, P., Edwards, F. A., et al. (2013) · Ecology Letters · doi:10.1111/ele.12162 · Cited by 662
Lu, Y., Zhou, G., Ewald, J., Pang, Z., Shiri, T., & Xia, J. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad407 · Cited by 623
Modelling Palaeoecological Time Series Using Generalised Additive Models
Simpson, G. L. (2018) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2018.00149 · Cited by 560
Clark, J. S., Nemergut, D., Seyednasrollah, B., Turner, P. J., & Zhang, S. (2017) · Ecological Monographs · doi:10.1002/ecm.1241 · Cited by 283
Metadata
- Authors
- Warton, D. I., Wright, S. T., & Wang, Y.
- Venue
- Methods in Ecology and Evolution
- Publisher
- Wiley
- Published
- 2011-06-06
- Volume
- 3
- Issue
- 1
- Pages
- 89-101
- ISSN
- 2041-210X (ISSN-L)
- OpenAlex
- W1488156261
- Cited by
- 1,276
- References
- 6
- FWCI
- 18.92
- Type
- journal article
- Language
- en
- Open access
- closed
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