Using Principal Components and Factor Analysis in Animal Behaviour Research: Caveats and Guidelines
Abstract
Principal component (PCA) and factor analysis (FA) are widely used in animal behaviour research. However, many authors automatically follow questionable practices implemented by default in general‐purpose statistical software. Worse still, the results of such analyses in research reports typically omit many crucial details which may hamper their evaluation. This article provides simple non‐technical guidelines for PCA and FA. A standard for reporting the results of these analyses is suggested. Studies using PCA and FA must report: (1) whether the correlation or covariance matrix was used; (2) sample size, preferably as a footnote to the table of factor loadings; (3) indices of sampling adequacy; (4) how the number of factors was assessed; (5) communalities when sample size is small; (6) details of factor rotation; (7) if factor scores are computed, present determinacy indices; (8) preferably they should publish the original correlation matrix.
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Digital signal processing methods-Fourier transforms, cepstral techniques, and principal component analysis-brought reproducibility and comparability to bioacoustics and made it possible to test hypotheses about vocal learning, hormonal effects, and neurophysiological control with new rigor.
“These methods brought reproducibility and comparability to a field that had long relied on description, making it possible to test hypotheses about vocal learning, hormonal effects, and neurophysiological control with new rigor”
From Listening forward: emerging roles of bioacoustics in ecology, evolution, and conservation (2026) · cites this paper as Budaev 2010
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“Fourier transforms broke calls into their frequency components (Davis 1986), ceps-tral techniques revealed subtle modulation patterns beyond human hearing (Randall 2017), and principal component analysis distilled massive datasets into biologically meaningful axes of variation (Budaev 2010).”
- Authors
- Budaev, S. V.
- Affiliations
- University of Sussex (GB)
- Corresponding author
- Budaev, Sergey V.
- ORCID
- Budaev, Sergey V.
- Venue
- Ethology
- Publisher
- Wiley
- Published
- 2010-04-13
- Volume
- 116
- Issue
- 5
- Pages
- 472-480
- ISSN
- 0179-1613 (ISSN-L)
- 1439-0310
- OpenAlex
- W2031168265
- Cited by
- 460
- References
- 39
- Citations by year
- 2026: 24 · 2025: 38 · 2024: 46 · 2023: 38 · 2022: 57 · 2021: 39 · 2020: 36 · 2019: 23 · 2018: 23 · 2017: 20 · 2016: 23 · 2015: 24 · 2014: 21 · 2013: 19 · 2012: 13
- FWCI
- 12.82
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Ethology (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Animal Behavior and Reproduction
- Keywords
- principal component analysis, factor analysis, animal behavior research, reporting guidelines, questionable research practices, sample adequacy, factor rotation, factor scores, correlation matrix, sample size, communality
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