Hasler Mario, Birr Tim, Hothorn Ludwig A
Lehrfach Variationsstatistik, Christian-Albrechts-University of Kiel, Kiel, Germany.
Department of Plant Diseases and Crop Protection, Institute of Phytopathology, Christian-Albrechts-University of Kiel, Kiel, Germany.
Biom J. 2025 Feb;67(1):e70019. doi: 10.1002/bimj.70019.
This paper proposes a general approach for handling multiple contrast tests for normally distributed data in the presence of partial heteroskedasticity. In contrast to the usual case of complete heteroskedasticity, the treatments belong to subgroups according to their variances. Treatments within these subgroups are homoskedastic, whereas treatments of different subgroups are heteroskedastic. New candidate as well as already existing approaches are described and compared by -simulations. Power simulations show that a gain in power is achieved when the partial heteroskedasticity is taken into account compared to procedures which wrongly assume complete heteroskedasticity. The new approaches will be applied to a phytopathological experiment.
本文提出了一种在存在部分异方差性的情况下处理正态分布数据多重对比检验的通用方法。与完全异方差性的常见情况不同，处理根据其方差属于不同的子组。这些子组内的处理是同方差的，而不同子组的处理是异方差的。通过模拟描述并比较了新的候选方法以及现有的方法。功效模拟表明，与错误假定完全异方差性的程序相比，考虑部分异方差性时功效会有所提高。新方法将应用于一项植物病理学实验。
