Multiple responses are common in industrial and scientific experimentation and a multivariate alternative to ordinary analysis of variance (ANOVA) is often required. Significance tests based on classical multivariate ANOVA (MANOVA) are, however, useless in many practical cases. The tests perform poorly in cases with several highly correlated responses and the method collapses when the number of responses exceeds the number of observations. 50-50 MANOVA is a method which handles this problem. Principal component analysis is an important part of the new methodology. The methodology was developed by Øyvind Langsrud at MATFORSK/NOFIMA.

The R-package ffmanova is available at CRAN: http://cran.r-project.org/web/packages/ffmanova/

Matlab code, a GUI and relevant references can be found here: http://www.langsrud.com/stat/

The software also contain rotation testing which is a framework for doing significance testing by computer simulations, ajustment of p-values and estimation of false discovery rates for multiple testing problems.