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Bartlett's test of sphericity and the KMO index were used to assess the suitability of the factor solution.
The Bartlett sphericity test and KMO index were used to assess the suitability of the factor solution.
A CFA was carried out on the validation sample in order to assess the suitability of the factor model proposed, comprising two correlated factors.
The Bartlett's test of sphericity (p < 0.001) made it possible to accept the identity of the matrix correlations for the ECOS-16 items, thus indicating the suitability of the factor analysis.
KMO and Bartlett's test showed that Kaiser-Meyer-Olkin measamplingsadequacyadequacy (KMO) at 0.804, and Bartlett's test of sphericity approx Chi-Square at 834.209 (P < 0.01), indicating the suitability of the factor analysis.
Parallel analysis is often recommended as the best method to assess the true number of factors [ 21].To assess the suitability of the factor solution, Bartlett's test of sphericity [ 22] should be significant, and the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy should be >0.6 [ 23].
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Bartlett's Test of Sphericity (χ2 = 5910.8, p < 0.001) and a Kaiser-Meyer-Olkin value of 0.88 confirmed the suitability of investigating the factor structure of the data.
These two measures of sampling adequacy imply the suitability of applying the factor analysis to the available data.
The suitability of the adaptation factor value adopted by the code is discussed and recommendations given.
Suitability of this factor is validated by comparing simulation data with field data.
The final diagnostic check for the suitability of the data for factor analysis was the factorability of R. Low bivariate correlations (< .30) indicate that factor analysis could be inappropriate for the given data.
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