What question did this study set out to answer?

The aim is to assess whether standard post-transformation analysis methods remain valid when data transformations inform the selection process.

June 1, 1984Open Access

The Analysis of Transformed Data

Key Points

The aim is to assess whether standard post-transformation analysis methods remain valid when data transformations inform the selection process.
Evaluated transformation selection implications from previous studies (Bickel and Doksum; Box and Cox).
Performed Bayesian analysis within normal-error linear model frameworks.
Used numerical examples to illustrate arguments.
The argument suggests that standard analysis methods may need adjustment post-transformation.
Findings highlight the importance of parameter interpretation in transformed data contexts.

Abstract

Abstract Recently it was suggested (Bickel and Doksum 1981) that when data are used to select a transformation, the post-transformation analysis of those data may need to be modified considerably from standard form so as to allow for the selection. We argue that common sense and the work of Box and Cox (1964) point to a contrary conclusion. Our argument is based on considerations of parameter interpretation and subsequent Bayesian analysis, within the context of fitting normal-error linear models. Numerical examples are used to illustrate the main points.

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