Canonical Analysis Button

Click the button to display the Canonical Analysis Startup Panel. Canonical analysis is used to investigate the relationship between two sets of variables (it is used as either a hypothesis testing or exploratory method).

The Canonical Analysis module offers a comprehensive implementation of canonical analysis procedures; it can process raw data files or correlation matrices and it computes all of the standard canonical correlation statistics (including eigenvectors, eigenvalues, redundancy coefficients, canonical weights, loadings, extracted variances, significance tests for each root, etc.) and a number of extended diagnostics. The scores of canonical variates can be computed for each case and visualized via integrated icon plots (they can also be appended to the data file). This module also includes a variety of integrated graphs (including plots of eigenvalues, canonical correlations, scatterplots of canonical variates, and many others).

Confirmatory analyses of structural relationships between latent variables can also be performed via the Structural Equation Modeling and Path Analysis (SEPATH) module; advanced stepwise and best-subset selection of predictor variables for MANOVA/MANCOVA designs (with multiple dependent variables) are available in the General Regression Models (GRM) module.