Application of 'robust' methods to the analysis of collaborative trial data using bacterial colony counts

We describe techniques for the application of two methods, robust to the presence of 'outliers', to the hierarchical analysis of variance of bacterial count data from collaborative trials. The techniques are tested against both artificially-generated data with known distributional parameters and actual trial results containing outliers. The relative merits of the robust methods are discussed in comparison with conventional ANOVA techniques.