Generalized linear models for the analysis of taguchi‐type experiments

Recent interest in Taguchi's methods have led to developments in joint analysis of the mean and dispersion from designed experiments. A commonly used method is the analysis of variance of the transformed data. However, a single transformation cannot necessarily produce the Normality, constancy of variance and linearity of systematic effects for the mean and dispersion models. We describe the use of generalized linear models for the analysis of such experiments and illustrate the methods with a data set.