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The interpretation of factor analysis is based on rotated factor loadings, rotated eigenvalues, and scree test.
The significance level for interpretation of factor loadings was 0.40.
Therefore, we set a threshold of 0.722 for interpretation of factor loadings, as suggested by Field (2009) [ 31].
Therefore, a sample size of 50 was set as minimum for PCA and 0.722 was set as a minimum for interpretation of factor loadings [ 31].
For an estimation of the stability of the factor structure, the FS parameter was calculated, which takes into account that the interpretation of factor loadings is dependent on sample size [ 45].
As suggested by Field (2009) [ 31], a sample size of 50 individuals can be satisfactory for factor analysis, if more restrictive thresholds for interpretation of factor loading are employed.
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This way of interpreting canonical variates is identical to the interpretation of factors in factor analysis [ 10].
Moll, R. H., Kamprath, E. J. & Jackson, W. A. Analysis and Interpretation of Factors Which Contribute to Efficiency of Nitrogen Utilization1.
The geological interpretation of factors yields insight into the main process, which may govern the distribution of hydrochemical variables (Davis and Dewiest 2006; Bahar and Reza 2010).
Interpretation of factors involves understanding the underlying dimension or concept that unifies the group of variables loading on it (Tabachnick and Fidell 2012).
As the field of accident studies has received much attention, and various theories have been developed for the interpretation of factors underlying an accident situation, most of the models will be presented in accident or actuarial data analysis contexts.
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