An Approached of Box-Cox Data Transformation to Biostatistics Experiment

SUMMARY

The Box-Cox family of transformation is a well-known approach to make data behave accordingly toassumption of linear regression and ANOVA. The regression coefficients, as well as theparameter? defining the transformation are generally estimated by maximum likelihood, assuminghomoscedastic normal error. In application of ANOVA for hypothesis testing in biostatistics scienceexperiments, the assumption of homogeneity of errors often is violating because of scale effects andthe nature of the measurements. We demonstrate a method of transformation data so that theassumptions of ANOVA are met (or violated to a lesser degree) and apply it in analysis of data frombiostatistics experiments. We will illustrate the use of the Box-Cox method by using MINITABsoftware.