Search
   >> Home >> Products >> Features >> Multivariate methods

Multivariate methods

Factor analysis

  • Works on datasets or correlation matrices
  • Principal-components factor
  • Principal factor
  • Interated principal factor
  • ML factors
  • Rotations
    • Orthogonal and oblique rotations
    • Kaiser normalization
    • Varimax, quartimax, oblimax, parsimax, equamax, and promax rotation
    • Minimum entropy rotation
    • Comrey's tandem
    • Rotate toward a target matrix
  • Anti-image correlation matrices
  • Kaiser–Meyer–Olkin measure of sampling adequacy
  • Loading plots , score plots , and scree plots
  • Squared multiple correlations
  • Bartlett scoring
  • Regression scoring

Principal components

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

Discriminant analysis

  • Linear
  • Quadratic
  • Logistic
  • kth nearest neighbor
  • Classification tables
  • Error rates

Zellner’s seemingly unrelated regression

  • Two-step or maximum likelihood estimates
  • Linear constraints
  • Breusch-Pagan test for independent equations

Multivariate linear regression

  • Breusch–Pagan test for independent equations

Canonical correlations

  • Correlation matrices
  • Loading matrices
  • Rotate raw coefficients, standard coefficients, or loading matrices
  • Compare rotated and unrotated coefficients or loadings
  • Plot canonical correlations

Tetrachoric correlations

  • Maximum likelihood or noniterative Edwards and Edwards estimator
  • Tetrachoric correlation coefficient and standard error
  • Exact two-sided significance level

Structural equation modeling (SEM) Updated

  • Complete implementation

Cluster analysis

  • Complete implementation

MANOVA

  • Complete implementation

Multivariate tests

  • One- and multisample
  • Means , covariances , and correlations
  • Tests of normality
    • Doornik–Hansen
    • Henze–Zirkler
    • Two by Mardia

Multidimensional scaling

  • Modern metric and nonmetric multidimensional scaling
  • Classic metric multidimensional scaling
  • Works with two-way data , proximity data in long format , and proximity data in a matrix
  • 33 similarity/dissimilarity measures
  • Coordinates of approximating configuration
  • Correlations between dissimilarities and distances
  • Kruskal stress measure
  • Shepard diagram
  • Plots of approximating Euclidean configuration

Correspondence analysis

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

Procrustes analysis

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

Biplots

  • Display your choice of any two biplot dimensions
  • Distinguish groups of data within the biplot
  • Display table of biplot coordinates
  • Generate new variables containing biplot coordinates

Hotelling’s T-squared

Cronbach’s alpha

  • Interitem correlations or covariances
  • Generate summative scale
  • Automatically reverse sense of variables

Additional resources

See New in Stata 13 for more about what was added in Stata 13.

The Stata Blog: Not Elsewhere Classified Find us on Facebook Follow us on Twitter LinkedIn Google+ Watch us on YouTube