Guttman-Kaiser criterion as a predictor of the number of common factors by K. A. Yeomans

Cover of: Guttman-Kaiser criterion as a predictor of the number of common factors | K. A. Yeomans

Published by University of Aston in Birmingham. Management Centre in Birmingham .

Written in English

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Statement[by] Keith A Yeomans and Paul A Golder.
SeriesWorking paper series -- No.185.
ContributionsGolder, P. A.
ID Numbers
Open LibraryOL21001802M

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Volume 31 Number 3 September Editor: Gopal K. Kanji A chart to describe and measure the effects of indus-trial inspection errors William Armstrong Enhancements to aid interpretation of probability plots W. Douglas Stirling The Guttman-Kaiser criterion as a predictor of the number of common factors Keith A.

Yeomans and Paul A. Given nuances in the computer programs, unwary researchers performing a common factor analysis on the same set of data can be expected to arrive at Cited by: 7.

This article evaluates the performance of the Guttman-Kaiser criterion in determining the number of significant components or factors in a correlation matrix. View Show abstract. The majority of these used the Kaiser–Guttman ‘Eigenvalues greater than one’ criterion, (Guttman, ; Kaiser,) to determine the number of factors.

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Description: The Statistician joined the Journal of the Royal Statistical Society as its Series D from the journal of the Institute of Statisticians after the merger of the two bodies in The journal was first published by the Institute in as The Incorporated is now a valuable resource for professional statisticians involved in industry, academic research and education.

Journal of the Royal Statistical Society: Series A (Statistics in Society) Journal of the Royal Statistical Society: Series B (Statistical Methodology).

Yeomans K. and Golder P. () The Guttman-Kaiser criterion as a predictor of the number of common factors. Statistic Zuckerman M. () Dimensions of sensation by: Brandy (PB) criterion (Štalec & Momirović, ). As a scientific result, PB criterion, unfortunately, was published only on Croatian language and is totally unknown outside of the borders of ex-Yugoslavia.

Most commonly used criterion is GK which simply states that the number of factors to retain is equal to the number of factors with. Trenerry C The Origin and Early History of Insurance New Jersey The Law from ECONOMICS econ at Pamukkale University - Denizli Vocational School of Social Sciences.

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Polish Psychological Bulletin The Journal of Committee for Psychological Sciences of Polish Academy of SciencesCited by: 1. Yeomans AK, Golder AP () The Guttman-Kaiser criterion as a predictor of the number of common factors. The Statistician – CrossRef Google Scholar Zereini F, Wiseman C, Beyer JM, Artelt S, Urban H () Platinum, lead and Cited by: 1.

Polish Psychological Bulletin The internal consistency of factors (Cronbach’s α) ranging from to P. The Guttman- Kaiser criterion as a predictor of the number of common factors. The Statistician, 3, Crossref Google Scholar. Życińska, J., Januszek, M.

Motivation at the global and motivation at Cited by: 2. () The Guttman-Kaiser criterion as a predictor of the number of common factors. Journal of the Royal Statistical Society, Series D, 31(3), – Cited by. In order to assess an appropriate number of factors, we took into account both the Guttman–Kaiser criterion (Guttman, ; Kaiser, ) and the scree test (Cattell, ).

The Kaiser–Meyer–Olkin measure of sampling adequacy and Bartlett’s test of sphericity were used to confirm that the items were suitable for factor by:   Thus, only one factor had an eigenvalue >1 (Guttman-Kaiser criterion). Parallel analysis suggested the retention of one factor, using as the criterion 99th percentile for eigenvalues obtained on 10, randomly generated data sets (the eigenvalues for the first two factors based on the randomly generated sets were and ).Cited by: 2.

In order to assess an appropriate number of factors, we took into account both the Guttman–Kaiser criterion (Guttman, ; Kaiser, ) and the scree test (Cattell, ). The Kaiser–Meyer–Olkin measure of sampling adequacy and Bartlett’s test of sphericity were used to confirm that the items were suitable for factor by:   The results of this analysis indicated two distinct dimensions according to the Guttman-Kaiser criterion for eigenvalues greater than 1 (Guttman, ).

The variance explained by the first dimension (academic adaptation; eigenvalue = ) was %. Factor loadings for the four items in this dimension were between andCited by: 9. The first two principal components, which were the only components to satisfy the Guttman-Kaiser criterion and to reach significance in the analyses reported below, jointly explained some 64% of variance of the full set of 10 original predictors.

Table 7 lists the loadings of the predictors on these PCs. The first component captures Cited by: The number of injury-related visits increased during the last 15 years and a % increment was observed.

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The Guttman-Kaiser criterion as a predictor of the number of common factors. The Statistician, pp. –[Google Scholar]), prompting concerns regarding its use within EFA. In addition to theoretical doubts, the Kaiser criterion also demonstrates practical by: - A study on the impact of trust and food risk communication.

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According to the Guttman-Kaiser rule (i.e., that eigenvalues should be > 1), one factor may be appropriate. However, the Guttman-Kaiser criterion has been criticized in recent decades (Nunnally & Bernstein, ).

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