Permutation tests for univariate or multivariate analysis of variance and regression

By Marti J. Anderson. 2001

1,469 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Plant Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/717acbf738208a96e369ca1176240bc2c4fc3543

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In Management Science and Operations Research

In Plant Science

In Statistics and Probability

Citations in the corpus

Niche differentiation among invasive crayfish and their impacts on ecosystem structure and functioning (2014, methodology): “We used permutational multivariate analysis of variance (PERMANOVA; Anderson, 2001) to test for effects of the experimental manipulations on the structure of benthic invertebrate assemblages using the PERMANOVA+ add-in to PRIMER ® version 6.1 (PRIMER-E Ltd, Plymouth, UK).”
Mass univariate analysis of event-related brain potentials/fields I: A critical tutorial review (2011, background): “Because such parameters have to be estimated from the data, permutation tests are only ‘‘asymptotically exact’’ for such tests (Anderson, 2001; Good, 2005).”
Patterns of landscape and assemblage structure along a latitudinal gradient in ocean climate (2012, methodology): “The calculated proportional measures of the extent of each bottom category were included as covariates in the permutational multivariate analysis of variance (PERMANOVA) model testing for differences in biogenic landscape structure, in order to remove the potential effect of the local reef topograph”
Remedies for pseudoreplication (2004, methodology): “A mixedeffects ANOVA-type model was deployed, but using design-based permutation to partition the variability in a dissimilarity matrix, rather than using a model based on assumptions of multivariate normality (Anderson, 2001a, 2001b).”
Local enhancement of epibenthic macrofauna by aquaculture activities (2008, background): “…of environmental changes in impact studies (Underwood & Chapman 2003), sampling multiple reference locations at multiple spatial scales is required to study the extent of the effects of point sources of disturbance (Archambault et al. 2001, Bishop et al. 2002) such as aquaculture facilities.”
Large scale experimental effects of three levels of sheep densities on an alpine ecosystem (2008, methodology): “Permutation tests with 499 permutations provided the p-values ( Anderson 2001, McArdle and Anderson 2001).”
Predation contributes to invasion resistance of benthic communities against the non-indigenous tunicate Ciona intestinalis (2011, methodology): “We performed permutational ANOVAs, using the statistical package PERMANOVA? to estimate with permutations the pseudo-F statistic, which is an analogue of the univariate Fisher’s F ratio (Anderson 2001; Anderson et al. 2008).”
Temporal and spatial variability in elemental composition of otoliths: implications for determining stock identity and connectivity of populations (2002, methodology): “The test statistic was then calculated as the ratio of the sum of squared Euclidean distances among groups divided by the sum of squared distances within groups, and is thus essentially an F ratio (Anderson 2001b).”
Multivariate and univariate asymmetrical analyses in environmental impact assessment: a case study of Mediterranean subtidal sessile assemblages (2005, methodology): “…univariate analyses in the assessment of impacts through comparisons of variance components and (2) to demonstrate the use of recently developed multivariate methods (i.e. distance-based permutational MANOVA, Anderson 2001a) in the analysis of multivariate species data in response to such a design.”
POLAR BEAR DIETS AND ARCTIC MARINE FOOD WEBS: INSIGHTS FROM FATTY ACID ANALYSIS (2008, methodology): “To account for this, we used randomization–permutation analyses (e.g., Efron and Tibshirani 1998, Good 2000, Anderson 2001, Beck et al. 2007) to examine spatial, temporal, and demographic differences in polar bear diet estimates.”