  The numerical availability of statistical inference methods for a modern and
robust analysis of longitudinal- and multivariate data in factorial experiments
is an essential element in research and education. While existing approaches
that rely on specific distributional assumptions of the data (multivariate
normality and/or characteristic covariance matrices) are implemented in
statistical software packages, there is a need for user-friendly software that
can be used for the analysis of data that do not fulfill the aforementioned
assumptions and provide accurate p-value and confidence interval estimates.
Therefore, newly developed statistical methods for the analysis of repeated
measures designs and multivariate data that neither assume multivariate
normality nor specific covariance matrices have been implemented in the freely
available R-package MANOVA.RM. The package is equipped with a graphical user
interface for plausible applications in academia and other educational purpose.
Several motivating examples illustrate the application of the methods.
