A method for obtaining randomized block designs in preclinical studies with multiple quantitative blocking variables.

Abstract

A method is proposed for block randomization of treatments to experimental units that can accommodate both multiple quantitative blocking variables and unbalanced designs. Hierarchical clustering in conjunction with leaf-order optimization is used to block experimental units in multivariate space. The method is illustrated in the context of a diabetic mouse… (More)
DOI: 10.1002/pst.445

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