Abstract
Mixed model packages can be used to analyze designed experiments with variance structures that allow for heterogeneity of variance between treatments. Such analyses are useful, when the error structure is complex. Alternatively, when a simple data transformation is found that stabilizes the variance, a standard ANOVA can be performed. Such a simple analysis has several practical advantages, including efficient use of error degrees of freedom and the facility to produce letter displays with a constant critical difference when data are balanced. It is therefore generally worth thoroughly exploring different data transformations before embarking on a more complex mixed model analysis.

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