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A note on Box-Cox transformation and application in microarray data  

Rahman, Mezbahur (Department of Mathematics and Statistics, Minnesota State University)
Lee, Nam-Yong (Department of Mathematics and Statistics, Minnesota State University)
Publication Information
Journal of the Korean Data and Information Science Society / v.22, no.5, 2011 , pp. 967-976 More about this Journal
Abstract
The Box-Cox transformation is a well known family of power transformations that brings a set of data into agreement with the normality assumption of the residuals and hence the response variable of a postulated model in regression analysis. Normalization (studentization) of the regressors is a common practice in analyzing microarray data. Here, we implement Box-Cox transformation in normalizing regressors in microarray data. Pridictabilty of the model can be improved using data transformation compared to studentization.
Keywords
Maximum likelihood estimates; moments for the ordered standard normal; variates; normality tests; Shapiro-Wilk W statistic;
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