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 language | English |
|---|---|
| Pages (from-to) | 991-1010 |
| Number of pages | 20 |
| Journal | IMA Journal of Management Mathematics |
| Volume | 36 |
| Issue number | 4 |
| Early online date | 27 Jun 2025 |
| DOIs | |
| Publication status | Published - Oct 2025 |
Keywords
- inverse normal transformations
- regression
- outliers
- small samples
- profile log-likelihood
Fingerprint
Dive into the research topics of 'The Development of Inverse Normal Transformations: A Review'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver