Factor analysis

• Works on datasets or correlation matrices
• Principal-components factor
• Principal factor
• Interated principal factor
• ML factors
• Rotations
• Anti-image correlation matrices
• Kaiser–Meyer–Olkin measure of sampling adequacy
• Squared multiple correlations
• Bartlett scoring
• Regression scoring

Principal components

• Works with datasets or correlation or covariance matrices
• Standard errors of eigenvalues and vectors
• Rotations
• Anti-image correlation matrices
• Kaiser–Meyer–Olkin measure of sampling adequacy
• Loading plots, score plots, scree plots
• Squared multiple correlations
• Orthogonal and oblique rotations
• Kaiser normalization
• Varimax, quartimax, oblimax, parsimax, equamax, promax rotation
• Minimum entropy rotation
• Comrey’s tandem
• Rotate toward a target matrix

Discriminant analysis

• Linear
• Quadratic
• Logistic
• k^th nearest neighbor
• Classification tables
• Error rates

Multidimensional scaling

• Modern metric and nonmetric multidimensional scaling
• Classic metric multidimensional scaling
• Works on datasets or matrices of distances
• 33 similarity/dissimilarity measures
• Coordinates of approximating configuration
• Correlations between dissimilarities and distances
• Kruskal stress measure
• Shepard diagram
• Plots of approximation Euclidian configuration

Correspondence analysis

• Two-way correspondence analysis
• Multiple correspondence analysis (MCA)
• Joint correspondence analysis (JCA)
• Work with cross-tabulations of categorical variables or matrices of counts
• Coordinates in column space
• Coordinates in row space (with two-way CA)
• Stacked (crossed) variables
• Chi-squared distances
• Inertia contributions
• Row and column profiles (conditional distributions)
• Fitted, observed, and expected correspondence tables
• Matrix of inertias (after JCA)
• Biplots
• Projection plots
• Correlations of profiles and loadings

Procrustes analysis

• Orthogonal, oblique, and unrestricted transformations
• Overlayed graphs comparing target variables and fitted values of source variables

Biplots

Canonical correlations

Tetrachoric correlations

Zellner’s seemingly unrelated regression

Multivariate linear regression

Hotelling’s T-squared

Tests for identifying multivariate outliers

Cluster analysis

MANOVA