The analysis of low dimensional factorial designs with possible interactions is a relevant
issue. Instead of the common pre-tests for interaction, a simultaneous inference procedure of …

In many scientific investigations, interest lies in studying the effects of several input variables
simultaneously on an output variable. Factorial experiments are ideally suited for such …

The analysis of unreplicated designs concentrates much of interest, since these designs
enable us to estimate the factorial effects using contrasts, while no degrees of freedom are …

New inference methods for the multivariate coefficient of variation and its reciprocal, the
standardized mean, are presented. While there are various testing procedures for both …

This tutorial emphasizes the role of differecnt types of experimental design in a multi–stage
investigation. In the initial phase group–screeningo can reveal the really important factors …

For paired comparison experiments involving options described by a common set of two-
level factors a new method for generating exact designs is presented. These designs allow …

Ever since the seminal work of RA Fisher and F. Yates, factorial designs have been an
important experimental tool to simultaneously estimate the treatment effects of multiple …

For unreplicated three-way layouts, the usual F-test can not be used for testing three-factor
interaction and it is common to base the analysis on the model without three-factor …

In this power study, ANOVAs of unbalanced and balanced 2 x 2 datasets are compared (N=
120). Datasets are created under the assumption that H1 of the effects is true. The effects are …

which all combinations of multiple factor levels are used, efficiently estimate factor effects
and detect interactions—desirable statistical qualities that can provide deep insight into a …