نوشته‌های جامعه‌شناسی

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Univariate and multivariate descriptives of variables:

• Univariate mean, variance, skewness, and kurtosis
• Multivariate skewness and kurtosis (Mardia, 1970)
• Var charts for ordinal variables

Dispersion matrices:

• User defined tipo matrix
• Covariance matrix
• Pearson correlation matrix
• Polychoric correlation matrix (Polychoric algorithm: Olsson ,1979a, 1979b; Tetrachoric algorithm: Bonett & Price, 2005) with smoothing algorithm (Devlin, Gnanadesikan, & Kettenring, 1975; Devlin, Gnanadesikan, & Kettenring, 1981)

Procedures for determining the number of factors/components to be retained:

• MAP: Minimum Average Partial Test (Velicer, 1976)
• PA: Parallel Analysis (Horn, 1965)
• Optimal PA. It is an implementation of Parallel Analysis where it is computed based on the same type of correlation matrix (i.e., Pearson or polychoric correlation) and the same type of underlying dimensions (i.e., components of factor) as defined for the whole analysis (Timmerman & Lorenzo-Seva, 2011)
• Hull method for selecting the number of common factors: this method aims to find a model with an optimal balance between model fit and number of parameters (Lorenzo-Seva & Timmerman, 2011)

Factor and component analysis:

• PCA: Principal Component Analysis
• ULS: Unweighted Least Squares factor analysis (also MINRES and PAF)
• EML: Exploratory Maximum Likelihood factor analysis
• MRFA: Minimum Rank Factor Analysis (ten Berge, & Kiers, 1991)
• Item Test Theory parameterization of factor solution
• Semi-confirmatory factor analysis based on orthogonal and oblique rotation to a (partially) specified target (Browne, 1972a, 1972b)
• Schmid-Leiman second-order solution (1957)
• Factor scores for continuous data (ten Berge, Krijnen, Wansbeek, & Shapiro, 1999), and expected a-posteriori (EAP) estimation of latent trait scores for ordinal data
• Person fit indices (Ferrando, 2009)

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