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Parallel analysis information


Parallel analysis, also known as Horn's parallel analysis, is a statistical method used to determine the number of components to keep in a principal component analysis or factors to keep in an exploratory factor analysis. It is named after psychologist John L. Horn, who created the method, publishing it in the journal Psychometrika in 1965.[1] The method compares the eigenvalues generated from the data matrix to the eigenvalues generated from a Monte-Carlo simulated matrix created from random data of the same size.[2]

  1. ^ Horn, John L. (June 1965). "A rationale and test for the number of factors in factor analysis". Psychometrika. 30 (2): 179–185. doi:10.1007/bf02289447. PMID 14306381. S2CID 19663974.
  2. ^ Mike Allen (11 April 2017). The SAGE Encyclopedia of Communication Research Methods. SAGE Publications. p. 518. ISBN 978-1-4833-8142-8.

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Parallel analysis

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coordinates, Velicer's (1976) minimum average partial, Horn's (1965) parallel analysis, and Ruscio and Roche's (2012) comparison data. Recent simulation...

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that have the same starting note (tonic) are called parallel keys and are said to be in a parallel relationship. For example, G major and G minor have...

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