DESIGNS FOR ACCUMULATION ANALYSIS AND RELATED METHODS
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概要
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Research in the behavioral sciences often leads to an analysis of ordered categorical data. Likewise the analysis of ordered categorical data is often an important activity in developing high quality products. Taguchi's Accumulation Analysis (<I>AA</I>) is one technique for exploring these data and essentially consists of using traditional analysis of variance methods on cumulative ordered categorical data. For <I>AA</I> in the multifactor setting, the ordered category data are generated using fractional factorial designs and the analysis proceeds by considering collapsed distributions under the design. To overcome some difficulties with <I>AA</I> Nair (1986) has suggested a modification to Taguchi's <I>AA</I> statistic. In addition Hamada and Wu (1990) have performed simulations to demonstrate some failings of <I>AA</I> and advocate alternative methods of analysis. In this paper we show that these deficiencies are not with the modified <I>AA</I> statistic but are due to the collapsed distributions under fractional designs. We also show that the use of fractional factorial designs with ordered categorical data can lead to one of five situations including the reversal of strong location effects. To counter the criticisms, alternative designs have been constructed which do not bias the modified <I>AA</I> statistic. These designs are not peculiar to the modified <I>AA</I> statistic but apply to other location and dispersion statistics such as those used in the Mann-Whitney-Wilcoxon test or Mood's dispersion test.
- 日本行動計量学会の論文
日本行動計量学会 | 論文
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