factortest performs the Bartlett's test for sphericity and the Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Both tests should be used prior to a factor or a principal component analysis.
Determinant of the matrix of correlation: This determinant will equal 1.0 only if all
correlations equal 0, otherwise the determinant will be less than 1.
Bartlett's test for sphericity: Calculates the determinant of the matrix of the sums of
products and cross-products (S) from which the intercorrelations matrix is derived. The
determinant of the matrix S is converted to a chi-square statistic and tested for
significance.
The null hypothesis is that the intercorrelation matrix comes from a population in which the
variables are noncollinear (i.e. an identity matrix), and that the non-zero correlations in
the sample matrix are due to sampling error.
Kaiser-Meyer-Olkin Measure of Sampling Adequacy: is an index for comparing the magnitudes of
the observed correlation coefficients to the magnitudes of the partial correlation
coefficients.
Large values for the KMO measure indicate that a factor analysis of the variables is a good
idea.
90 or above, excelent
80 or above, meritorious
70 or above, middling
60 or above, mediocre
50 or above, miserable; and
below .50, unacceptable.
Box,G.E.P.(1949) "A general distribution theory for a class of likelihood criteria."
Biometrica, 36: 317-346.
Cureton, E.E., & D'Agostino, R.B. (1983). Factor analysis: An applied approach. Hillsdale, NJ:
Erlbaum.
This module may be installed from within Stata by typing "ssc install factortest". Windows users should not attempt to download these files with a web browser.
factor analysis; principal components; sphericity; sampling adequacy;
João Pedro Azevedo
[email protected]
World Bank
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