The Development of Inverse Normal Transformations: A Review

  • Terence Cooke*
  • , Roszaini Haniffa
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

This paper reviews the literature on inverse normal transformations (INTs), focusing on four primary methods used in regression analysis. We examine the statistical context, derivation and classification of INTs, as well as their applications in business and management. By reflecting on key studies that have shaped the development of these methods, we evaluate whether the choice of INT significantly affects inferential accuracy, particularly when sample sizes are small. We conclude by proposing standardized transformation parameters that bridge theoretical advances and practical decision-making.

Original languageEnglish
Pages (from-to)991-1010
Number of pages20
JournalIMA Journal of Management Mathematics
Volume36
Issue number4
Early online date27 Jun 2025
DOIs
Publication statusPublished - Oct 2025

Keywords

  • inverse normal transformations
  • regression
  • outliers
  • small samples
  • profile log-likelihood

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