MANCOVAN

Fixed a bug in mStepwise.m that sometimes caused p-values to be returned in sorted order, made the canonical coding of the design matrix described in mG2X.m the default, and added options for sigma-restricted and over-determined coding.

Revision 492 uses a sigma-restricted coding scheme to generate design matrices because the resulting regression coefficients are much easier to interpret. It also includes several improvements to the t-test engine, mT.m.

These tools are now compatible with GNU Octave Version 3.2.2. In addition, the way mStepwise.m removes terms has been improved and a few convenience functions have been added for finding and using model terms.

Removed the temp parent directory from the ZIP file.

This update replaces the single function, MANCOVAN, with a suite of tools that not only implement this model, but also provide multivariate stepwise regression, t-tests, customization of the design matrix, and much more.

Changed ANCOVA to ANCOVAN in the description.

Added options to test for covariate-covariate and group-covariate interactions, an option to print figures to PDF, and a debug mode that interactively displays the full and reduced design matrices associated with each test.

Removed the dependence on the Statistics Toolbox. This means that ANOVA, ANCOVA, ANOVAN, ANCOVAN, MANOVA, MANCOVA, MANOVAN, and MANCOVAN can all be performed with a single function with no dependencies other than Matlab itself.

Added an option to evaluate group-group interactions and added additional figures, verbose output, and comments. Confirmed that the values returned in pANCOVA are identical to those returned by anovan in the absence of covariates.

The Bayesian information criterion and SVD results can now be recovered as part of the output and a myriad of useful publication-quality graphics may now be generated automatically. See the help text for details.

Added an automatic dimensionality-reduction step based on the Bayesian information criterion for cases in which the number of columns of Y exceed the number of rows by a number that causes the test statistic to fail.