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.
翻译:对对照控制进行的治疗或剂量的多数比较是由最初的Dunnett单步程序(cite{Dunnett1955})进行的,该程序既提供了调整的p值,又提供了对控制差异的同步置信间隔。受权力争论的驱使,建议了在控制中抽样规模较大的不平衡设计。当利息处理或控制方面出现较大差异时,可以如预期的那样降低相关的每帕权力。然而,如果非受影响治疗组的差异增加,例如,在最高剂量(非常重要)中,对其余感兴趣的治疗组也降低了每帕的能量。I.e. 可能严重扭曲关于某些比较重要性的决定。为避免这种恶劣的属性,对差异的三次修改由模拟研究与原Dunett程序进行比较。对于中小样本规模,可以建议进行Welch型的修改。对于中低样本大小而言,使用三明治估计器而不是普通平均正方位面积的估算器是有用的。相关的CRAN软件包被严重扭曲了。为避免了这种恶劣的特性,我们建议用原始的常规研究来取代它。</s>