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.
Hedges
Alan John
AJ
University of Bristol, Department of Cellular and Molecular Medicine, University Walk, Bristol, Bristol BS8 1TD, United Kingdom. A.Hedges@bris.ac.uk
Jarvis
Basil
B
D000704:Analysis of Variance; D015169:Colony Count, Microbial / Q000379:methods* / Q000592:standards; D003198:Computer Simulation; D007753:Laboratories / Q000592:standards; D015337:Multicenter Studies as Topic / Q000379:methods*; D015203:Reproducibility of Results