Using Principal Components and Factor Analysis in Animal Behaviour Research: Caveats and Guidelines
Publication Type: |
Journal Article |
Year of Publication: |
2010 |
Authors: |
S. V. Budaev |
Publication/Journal: |
Ethology |
Keywords: |
animal behaviour research, FA, pca, statistics |
ISBN: |
0179161314390310 |
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.