Analysis of Variance (Anova)
By Robert L. Miller, C. Acton, Deirdre A. Fullerton, John Maltby, J. Campling. The SAGE Encyclopedia of Research Design, 2022
841 citations recorded by the source corpus.
Analysis of variance (ANOVA) is a type of general linear model suitable for factorial designs, in which one is interested in the main effects of, and interactions between, one or more factors. ANOVA assumes a spherical error covariance, and violations such as correlation induced by repeated measures from the same subjects, or inhomogeneous variance across conditions, require either post hoc corrections to the degrees of freedom, partitioning of the error into separate error terms, or explicit modeling of the error covariance.
Subfields: Computer Networks and Communications, Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/851effa3e56b476849716f7d1e96dbb2db072822
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Citations in the corpus
- Structural Similarity for Improved Transfer in Reinforcement Learning (2022, neutral): “We conduct an Analysis of Variance (ANOVA) test for each of the three independent factors used in creating the environments [19].”
- ANOVA–principal component analysis and ANOVA–simultaneous component analysis: a comparison (2011, methodology): “The multivariate model considered here is an extension of two‐way ANOVA to many variables [1,2].”
- Are you an energy saver at home? The personality insights of household energy conservation behaviors based on theory of planned behavior (2021, methodology): “It is used to test the significance of the difference in the mean of the dependent variable and determine the factors that will affect the experiment results (Kaufmann and Schering, 2014).”