Principal Component Analysis 2 Components Number Selecting
Channel: Алексей Ротмистров
Date: 2018-02-11

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Launching the FA. Preliminary, Bartlett's test and KMO test show whether the correlation matrix is suitable for searching for sheaves of pairwise linear correlations (that is, whether the FA is applicable in the considering case). If KMO value is greater than 0.5 and the null hypothesis in Bartlett's test regarding the data sphericity is rejected (sig. is less than the conventional significance level) FA is applicable. A Communality table shows what percentage of the indicators' variance is explained by the component model. The number of components is determined by the Kaiser criterion by default (there remain components that "explain" more than one eigenvalue, that is, more than one abstract indicator).
Empirical base -- Parents' motives https://drive.google.com/file/d/1jXFE9vU77W9F4eKThY5WbR0HhkDjvyCj/view?usp=sharing
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