The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Analysis of Variance: The Fundamental Concepts
Abstract
Analysis of variance (ANOVA) is a statistical test for detecting differences in group means when there is one parametric dependent variable and one or more independent variables. This article summarizes the fundamentals of ANOVA for an intended benefit of the clinician reader of scientific literature who does not possess expertise in statistics. The emphasis is on conceptually-based perspectives regarding the use and interpretation of ANOVA, with minimal coverage of the mathematical foundations. Computational examples are provided. Assumptions underlying ANOVA include parametric data measures, normally distributed data, similar group variances, and independence of subjects. However, normality and variance assumptions can often be violated with impunity if sample sizes are sufficiently large and there are equal numbers of subjects in each group. A statistically significant ANOVA is typically followed up with a multiple comparison procedure to identify which group means differ from each other. The article concludes with a discussion of effect size and the important distinction between statistical significance and clinical significance.
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Cites
An analysis of variance test for normality (complete samples)
SHAPIRO, S. S., & WILK, M. B. (1965) · Biometrika · doi:10.1093/biomet/52.3-4.591 · Cited by 23,480
An Analysis of Variance Test for Normality (Complete Samples)
Shapiro, S. S., & Wilk, M. B. (1965) · Biometrika · doi:10.2307/2333709 · Cited by 23,469
Statistical methods in psychology journals: Guidelines and explanations.
Wilkinson, L., & Task Force on Statistical Inference (1999) · American Psychologist · doi:10.1037/0003-066x.54.8.594 · Cited by 2,791
Eta-squared and partial eta-squared in fixed factor anova designs
Cohen, J. (1973) · Educational and Psychological Measurement · doi:10.1177/001316447303300111 · Cited by 1,333
Cautionary note on reporting eta-squared values from multifactor ANOVA designs.
Pierce, C. A., Block, R. A., & Aguinis, H. (2004) · Educational and Psychological Measurement · doi:10.1177/0013164404264848 · Cited by 584
Cited by
Nanda, A., Mohapatra, D. B. B., Mahapatra, A. P. K., Mahapatra, A. P. K., & Mahapatra, A. P. K. (2021) · International Journal of Statistics and Applied Mathematics · doi:10.22271/maths.2021.v6.i1a.636 · Cited by 281
Metadata
- Authors
- Sawyer, S. F.
- Venue
- Journal of Manual & Manipulative Therapy
- Publisher
- Informa UK Limited
- Published
- 2009-04
- Volume
- 17
- Issue
- 2
- Pages
- 27E-38E
- ISSN
- 1066-9817 (ISSN-L)
- 2042-6186
- OpenAlex
- W2044233072
- Cited by
- 382
- References
- 5
- FWCI
- 0.55
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
