Factor Analysis (Statistical Associates "Blue Book" Series Book 15)
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Factor Analysis (Statistical Associates "Blue Book" Series Book 15)
FACTOR ANALYSIS
Factor analysis is used to uncover the latent structure (dimensions) of a set of variables. It reduces attribute space from a larger number of variables to a smaller number of factors and as such is a "non-dependent" procedure (that is, it does not assume a dependent variable is specified). Illustrated with numerous how-to figures, output tables, and examples for SPSS, SAS, and Stata.
New in the 2013 edition: 50% additional coverage; now covers categorical (nonlinear) categorical principal components analysis as well as principal components and principal factor analysis for continuous variables; thorough restructuring for better readability; new coverage for Stata as well as SPSS and SAS; coverage of factor loading plots; expanded discussion of rotation methods; hyperlinking of FAQs to key words in text; numerous other updates.
FACTOR ANALYSIS Table of Contents Overview8 Data10 Key Concepts and Terms10 Exploratory factor analysis (EFA)10 Exploratory vs. confirmatory factor analysis (CFA)10 Factor Analytic Data Modes11 R-mode factor analysis11 Q-mode factor analysis11 Other rarer modes of factor analysis12 Types of factor extraction13 Principal components analysis (PCA)13 Principal factor analysis (PFA)14 PCA and PFA compared14 Other Extraction Methods16 Types of factor rotation17 Rotation methods17 No rotation18 Varimax rotation19 Quartimax rotation20 Equamax rotation21 Direct oblimin (oblique) rotation22 Promax rotation23 Other rotation methods24 Summary24 Factor analysis in SPSS24 Data setup24 The "Factor" dialog24 Descriptives and Options25 Extraction26 Rotation27 Factor Scores28 Statistical output in SPSS29 Factor loadings29 Plot of factor loadings (factor space plot)31 Factor, component, pattern, and structure matrices33 Communality34 Uniqueness36 Eigenvalues36 Extraction sums of squared loadings37 Trace37 Factor scores38 Bartlett scores39 Saving factor scores40 Criteria for number of factors to model40 Parallel analysis42 Other Criteria43 Using reproduced correlation residuals to validate the choice of number of factors43 Summary44 Factor analysis in SAS44 SAS interface44 SAS syntax45 Rotation methods in SAS47 Statistical output in SAS48 Factor loadings in SAS output48 SAS output for communalities48 SAS output for eigenvalues48 SAS scree plot output49 SAS factor loadings plots51 Factor analysis in Stata52 Stata interface52 Importing data into Stata53 Stata syntax55 Statistical output in Stata58 Stata output for eigenvalues58 Factor loadings in Stata output59 Stata output for communalities59 Stata scree plot output59 Stata loading plots60 Categorical principal components analysis (CATPCA)62 Overview62 SPSS categorical principal components analysis63 Data considerations63 CATPCA user interface in SPSS63 The “Optimal Scaling†dialog63 The main CATPCA dialog64 The “Discretize†button dialog66 The “Missing†button dialog67 The “Options†button dialog68 The “Output†button dialog70 The “Save†button dialog72 The “Object†button dialog72 The “Category†button dialog73 The “Loading†button dialog75 SPSS CATPCA statistical output75 The “Model Summary†table75 The “Component Loadings†table77 The “Component Loadings†plot79 The “Variance Accounted For†table80 The “Object Points Labeled by Casenumbers†plot81 The “Object Scores†table82 The “Biplot Component Loadings and Objects†plot83 The “Quantifications†table84 The “Category Points†plot85 The “Projected Centroids†table and plot87 SAS categorical principal components analysis89 Overview89 SAS syntax89 The PROC PRINQUAL procedure90 SAS PROC PRINQUAL output92 Principal components analysis of transformed data94 Stata categorical principal components analysis97 Overview97 Example98 The polychoric correlation matrix98 The “Principal component analysis†table99 The “Scoring Coefficients†table100 and 31 more pages of topics Pagecount: 131