The use of box-cox transformations in the development of multivariate tolerance regions with applications to clinical chemistry

Richard A. Rode, Vernon Chinchilli

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Attempts often have been made to transform clinical and laboratory data to approximate normality for the purpose of developing either univariate “normal” ranges or multivariate reference ranges in the “supposedly healthy” population. For many of these transformations to be successful, it has been necessary to arbitrarily delete outlier values with no scientific justification for doing so. In this article, construction principles used in the determination of these ranges are reviewed. In addition, the Box-Cox family of power transformations is proposed as a means of obtaining an approximate multivariate normal distribution without an arbitrary deletion of outlier values. This method will allow for the construction of reference ranges for the clinical and laboratory variables of interest.

Original languageEnglish (US)
Pages (from-to)23-30
Number of pages8
JournalAmerican Statistician
Volume42
Issue number1
DOIs
StatePublished - Jan 1 1988

Fingerprint

Box-Cox Transformation
Chemistry
Tolerance
Range of data
Outlier
Power Transformation
Multivariate Normal Distribution
Justification
Normality
Deletion
Univariate
Transform
Necessary
Outliers
Box-Cox transformation
Arbitrary
Box-Cox
Power transformation
Multivariate normal distribution

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Mathematics(all)
  • Statistics, Probability and Uncertainty

Cite this

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The use of box-cox transformations in the development of multivariate tolerance regions with applications to clinical chemistry. / Rode, Richard A.; Chinchilli, Vernon.

In: American Statistician, Vol. 42, No. 1, 01.01.1988, p. 23-30.

Research output: Contribution to journalArticle

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