A Two-Step Approach for Transforming Continuous Variables to Normal: Implications and Recommendations for IS Research

This article describes and demonstrates a two-step approach for transforming non-normally distributed continuous variables to become normally distributed. Step 1 involves transforming the variable into a percentile rank, which will result in uniformly distributed probabilities. The second step appli...

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Bibliographic Details
Published in:Communications of the Association for Information Systems 2011, Vol.28, p.4
Main Author: Templeton, Gary F.
Format: Article
Language:English
Subjects:
Continuity (mathematics)
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Summary:This article describes and demonstrates a two-step approach for transforming non-normally distributed continuous variables to become normally distributed. Step 1 involves transforming the variable into a percentile rank, which will result in uniformly distributed probabilities. The second step applies the inverse-normal transformation to the results of Step 1 to form a variable consisting of normally distributed z-scores. The approach is little-known outside the statistics literature, has been scarcely used in the social sciences, and has not been used in any IS study. The article illustrates how to implement the approach in Excel, SPSS, and SAS and explains implications and recommendations for IS research.
ISSN:1529-3181
1529-3181
DOI:10.17705/1CAIS.02804