Allen and Hubbard (1986) increased the accessibility
of parallel analysis for principal components
applications by developing an equation to predict
mean eigenvalues of random data matrices with
unities in the diagonals. Two recent studies have
shown, however, that Allen and Hubbard’s procedure
may yield degenerate solutions-that is, solutions
in which succeeding eigenvalues are larger
than preceding eigenvalues. The parameters of
sample size and number of variables within which
the Allen and Hubbard equation degenerates are
documented. Implications for the use of this
procedure are discussed. Index terms: exploratory
factor analysis, factor extraction, parallel analysis,
principal components analysis, rules for factor
Cota, Albert A, Longman, R. Stewart, Holden, Ronald R & Fekken, G. Cynthia. (1991). Anomalies in the Allen and Hubbard parallel analysis procedure. Applied Psychological Measurement, 15, 95-97. doi:10.1177/014662169101500111
Cota, Albert A.; Longman, R. Stewart; Holden, Ronald R.; Fekken, G. Cynthia.
Anomalies in the Allen and Hubbard parallel analysis procedure.
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