Abstract
Several flexible, one-parameter classes of transformations have been proposed for random variables taking values in [0, 11. This article studies a transformation family based on the incomplete beta function that, unlike other families proposed, includes the arcsin squareroot transformation, the logit transformation, and the identity transformation. Applications to regression, correlation analysis, and response-surface analysis are presented. A new method of comparing members of different transformation families is derived, and connections with generalized linear models are discussed. The article concentrates on continuous data rather than binomial data.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 72-81 |
| Number of pages | 10 |
| Journal | Technometrics |
| Volume | 35 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1993 |
Keywords
- Incomplete beta function
- Normalizing transformation
- Variance-stabilizing transformation
ASJC Scopus subject areas
- Modeling and Simulation
- Applied Mathematics
- Statistics and Probability