On the efficacy of the rank transformation in stepwise logistic and discriminant analysis.


Journal Article

We have evaluated the performance of four stepwise variable selection procedures commonly used in medical and epidemiologic research. The four procedures are discriminant and logistic regression and their rank transformed versions, where the independent variables are replaced by their ranks. We generated, by computer, data for two groups from several distributions with a variety of sample sizes and covariance matrices. The two ranking procedures each increased the chance of correctly selecting those variables related to group membership for data generated from log-normal or contaminated distributions. For normally distributed data the ranking procedure had little effect on variable selection. Rank transformed discriminant analysis and rank transformed logistic regression were equally effective in selecting variables when sample sizes exceeded 100. Rank transformed discriminant analysis was superior for smaller data sets. We discuss the implications of the results of this study for clinical and epidemiologic research.

Full Text

Cited Authors

  • O'Gorman, TW; Woolson, RF

Published Date

  • January 1, 1993

Published In

Volume / Issue

  • 12 / 2

Start / End Page

  • 143 - 151

PubMed ID

  • 8446809

Pubmed Central ID

  • 8446809

Electronic International Standard Serial Number (EISSN)

  • 1097-0258

International Standard Serial Number (ISSN)

  • 0277-6715

Digital Object Identifier (DOI)

  • 10.1002/sim.4780120206


  • eng