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Educational and Psychological Measurement
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A Monte Carlo Study of Testing the Significance of Correlation Matrices

N. Clayton Silver

Tulane University

William P. Dunlap

Tulane University

A Monte Carlo simulation was conducted to examine the Type I error rates and power of the tests by Bartlett; Brien, Venables, James, and Mayo; Kullback; and Steiger of the null hypothesis that a correlation matrix equals the identity matrix. Such tests are often recommended as preliminary procedures before performing factor analysis or evaluating the hypothesis of equal correlations. The Brien et al. procedure was found to be the most powerful test while maintaining stable empirical alpha values.

Educational and Psychological Measurement, Vol. 49, No. 3, 563-569 (1989)
DOI: 10.1177/001316448904900306
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This article has been cited by other articles:


Home page
 Educational and Psychological MeasurementHome page
R. T. Fouladi and J. H. Steiger
Tests of Multivariate Independence: A Critical Analysis of "A Monte Carlo Study of Testing the Significance of Correlation Matrices" by Silver and Dunlap
Educational and Psychological Measurement, December 1, 1993; 53(4): 927 - 932.
[Abstract]

Home page
 Educational and Psychological MeasurementHome page
N. C. Silver and W. P. Dunlap
A Fortran IV Program for Testing the Significance of Correlation Matrices
Educational and Psychological Measurement, September 1, 1990; 50(3): 597 - 599.
[Abstract]