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The final results extracted by the factor analysis will attempt to identify how certain gender attitudes are dependent or not of the territorial architecture.
Two latent factors were suggested by the factor analysis: one related to Schneiderian hallucinatory experiences and passivity phenomena, and another comprised of the three items on thought control (thought broadcasting, thought withdrawal, and thought insertion).
Under this modeling framework, we reduced the high-dimensional responses to low-dimensional latent factors by the factor analysis model, and then we used the multivariate linear mixed model to study the longitudinal trends of these latent factors.
Comparing the variables created by the factor analysis in Table 7 with the variables presented in the main analysis (Table 2 in the main part of the paper), we see that the two sets of variables are quite similar.
In this section, we will repeat the analysis done in the main part of the paper, but instead of using the attitude variables from the main analysis, we will use the factors created by the factor analysis as variables in the regressions.
Subsequently, the random eigenvalues have to be compared to the eigenvalues produced by the factor analysis.
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Gathered data have been analyzed by applying the Factor Analysis for Mixed Data (FMDA), the Hierarchical Clustering on Principal Components (HCPC); as well as Chi2 test of independence, ANOVA and Kruskal-Wallis tests for measuring dependencies or relations among variables.
We were able to investigate this possibility by comparing the factor analysis derived symptom domains observed in the first psychotic episode with that of a recurrence episode.
Therefore, their modal structure was identified by means of the factor analysis for most of the separated air masses.
We then explored the Kaiser-Guttman criterion by re-running the factor analysis with 10 factors specified.
This last appreciation is further supported by results of the factor analysis that clearly identified two main factors.
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