Permutation Methods: A Distance Function Approach

By Shin-Ta Liu. Technometrics, 2002

434 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/b50cef255846a34202543be87ac748618a3f7f20

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Citations in the corpus

Changes in soil microbial community structure and metabolic activity following conversion from native Pinus massoniana plantations to exotic Eucalyptus plantations (2013, methodology): “The Monte Carlo permutation test (999 times) was used to test the significance of the statistical results (Mielke and Berry, 2001; Weand et al., 2010).”
Causal Inference without Balance Checking: Coarsened Exact Matching (2012, background): “Methods violating this principle lead to less robust inferences with suboptimal and highly counterintuitive properties (Mielke and Berry, 2007).”
Ambiguities inherent in sums-of-squares-based error statistics (2009, background): “Sums-of-squares-based error or deviation statistics are inappropriate measures of the average or typical error or deviation because their values are often counterintuitive (Mielke and Berry, 2001) or ambiguous (Willmott and Matsuura, 2005, 2006).”
Discrepancy Analysis of State Sequences (2011, methodology): “In addition, the data contains a “weight” variable for adjusting for response bias.”
The resting brain: unconstrained yet reliable. (2009, methodology): “We applied permutation tests to assess the significance of the resulting Kendall’s W values (see Supporting Information; Legendre and Lapointe 2004; Mielke and Berry 2007).”
A MANOVA STATISTIC IS JUST AS POWERFUL AS DISTANCE-BASED STATISTICS, FOR MULTIVARIATE ABUNDANCES (2004, neutral): “MRPP§ g Wk,r c O k k51 nk 1 2 2 Mielke et al. (1976)”
Double-check: validation of diagnostic statistics for PLS-DA models in metabolomics studies (2011, methodology): “To overcome these problems and to give a measure of the statistical significance of the diagnostic statistics (P-value), a permutation test was introduced (Lindgren et al. 1996; Golland et al. 2005; Mielke and Berry 2007; Pesarin and Salmaso 2010).”
Global diversity and distribution of arbuscular mycorrhizal fungi (2011, positive): “In addition, we tested for specific differences in fungal community composition among continents, paleocontinents, plant communities, soil temperature, and soil moisture using multiple response permutation procedures (MRPP) with BrayeCurtis dissimilarity matrices (Mielke and Berry, 2007).”
Landscape matrix and species traits mediate responses of Neotropical resident birds to forest fragmentation in Jamaica (2010, methodology): “…species composition was compared among matrix types using multiresponse permutation procedure (MRPP; based on Bray-Curtis distance matrix), which compares distances among samples within a priori groups from those derived from a randomization procedure (Mielke and Berry 2001, McCune and Grace 2002).”
Effect size, confidence interval and statistical significance: a practical guide for biologists (2007, methodology): “There is no consensus on how to deal with this problem although several procedures have been proposed as non-parametric measures of effect size (e.g. Mielke & Berry, 2001; Johnston, Berry & Mielke, 2004; reviewed in Grissom & Kim, 2001).”