The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Using false discovery rates for multiple comparisons in ecology and evolution
Abstract
Summary: 1. Ecologists and evolutionary biologists often need to simultaneously evaluate the significance of multiple related hypotheses. Multiple comparisons need to be corrected to avoid inappropriately increasing the number of null hypotheses that are wrongly rejected. The traditional method of correction involves Bonferroni‐type multiple comparison procedures which are highly conservative, tending to increase the number of wrong rejections of true hypotheses as the number of hypotheses being simultaneously tested increases. 2. Newer procedures which are based on False Discovery Rates and which do not suffer the same loss of power as traditional methods are described. Algorithms and spreadsheet‐based software routines for three procedures which are especially useful in ecology and evolution are provided. 3. The strengths and potential pitfalls of FDR‐based analysis and of presenting results as FDR‐adjusted P‐values are discussed with reference to traditional methods such as the sequential Bonferroni correction. 4. FDR‐based multiple comparison procedures should be more widely adopted because they are often more appropriate than traditional methods for identifying truly significant results.
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
An improved Bonferroni procedure for multiple tests of significance
SIMES, R. J. (1986) · Biometrika · doi:10.1093/biomet/73.3.751 · Cited by 2,396
Cited by
Getting Under the Hood: How and for Whom Does Increasing Course Structure Work?
Eddy, S. L., & Hogan, K. A. (2014) · CBE—Life Sciences Education · doi:10.1187/cbe.14-03-0050 · Cited by 553
“Thus, the model used for each question was: Survey response = Intercept + β*SATI.Comb + β*Treat. p Values were adjusted to account for false discovery rates due to multiple comparisons (Pike, 2011).”
MethodInfluentialDetecting and avoiding likely false‐positive findings – a practical guide
Forstmeier, W., Wagenmakers, E., & Parker, T. H. (2017) · Biological Reviews · doi:10.1111/brv.12315 · Cited by 436
Ma, Y., Belyaeva, O. V., Brown, P. M., Fujita, K., Valles, K., Karki, S., de Boer, Y. S., Koh, C., Chen, Y., Du, X., et al. (2019) · Hepatology · doi:10.1002/hep.30350 · Cited by 312
Transparency in Ecology and Evolution: Real Problems, Real Solutions
Parker, T. H., Forstmeier, W., Koricheva, J., Fidler, F., Hadfield, J. D., Chee, Y. E., Kelly, C. D., Gurevitch, J., & Nakagawa, S. (2016) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2016.07.002 · Cited by 201
D’Cruze, N., Khan, S., Carder, G., Megson, D., Coulthard, E., Norrey, J., & Groves, G. (2019) · Animals · doi:10.3390/ani9060332 · Cited by 100
Metadata
- Authors
- Pike, N.
- Venue
- Methods in Ecology and Evolution
- Publisher
- Wiley
- Published
- 2010-08-23
- Volume
- 2
- Issue
- 3
- Pages
- 278-282
- ISSN
- 2041-210X (ISSN-L)
- OpenAlex
- W1519128746
- Cited by
- 634
- References
- 3
- FWCI
- 14.01
- Type
- journal article
- Language
- en
- Open access
- closed
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