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We accommodated with these hypotheses by choosing a factor analysis based on tetrachoric correlations as our method.
In the factor analyses based on tetrachoric correlations, the dichotomous diagnoses were recalculated into continuous variables (see methods chapter), i.e. the illness data used for the exploratory analyses also reflect predispositions for illnesses as assumed by correlations between diagnosis groups.
Internal consistency alpha based on tetrachoric correlations for the NPI in this sample was 0.83.
Internal consistency alpha based on tetrachoric correlations for the present sample ranged from 0.69 to 0.94 for the AUDADIS scales.
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Factor analysis was based on tetrachoric correlation matrices [ 22], and the factors were extracted using the principal factor method.
In short, correlations between diagnosis groups were analysed by exploratory factor analysis based on a tetrachoric correlation matrix.
In the above mentioned paper [ 15], correlations between diagnosis groups were analyzed by exploratory factor analysis based on a tetrachoric correlation matrix.
The implemented factor analyses were based on polychoric correlations, an extension of the tetrachoric correlation between two bivariate distributed continuous variables measured at an ordinal level.
For instance, the dimensional analyses of the dichotomous APZ items were based on Pearson correlations among the items, which, unlike tetrachoric correlations, can be severely attenuated if the items differ markedly by their difficulties [27].
Partial intraclass correlation calculated based on intraclass correlations method 1 [22].
It was hence based on polychoric correlations.
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