  Most comparisons of treatments or doses against a control are performed by
the original Dunnett single step procedure \cite{Dunnett1955} providing both
adjusted p-values and simultaneous confidence intervals for differences to the
control. Motivated by power arguments, unbalanced designs with higher sample
size in the control are recommended. When higher variance occur in the
treatment of interest or in the control, the related per-pairs power is
reduced, as expected. However, if the variance is increased in a non-affected
treatment group, e.g. in the highest dose (which is highly significant), the
per-pairs power is also reduced in the remaining treatment groups of interest.
I.e., decisions about the significance of certain comparisons may be seriously
distorted. To avoid this nasty property, three modifications for heterogeneous
variances are compared by a simulation study with the original Dunnett
procedure. For small and medium sample sizes, a Welch-type modification can be
recommended. For medium to high sample sizes, the use of a sandwich estimator
instead of the common mean square estimator is useful. Related CRAN packages
are provided. Summarizing we recommend not to use the original Dunnett
procedure in routine and replace it by a robust modification. Particular care
is needed in small sample size studies.
