A note on cross-validating prediction equations

Neil J. Dorans, Fritz Drasgow

Research output: Contribution to journalArticlepeer-review

Abstract

Cross-validation typically refers to the application of regression weights derived in one sample (the derivation sample) to a different sample (the validation sample) to investigate the stability of relationships based on the original weights. When the standard cross-validation paradigm is thought to reflect accurately the use of a prediction equation in practice, the researcher should use an appropriate cross-validation strategy. Two superficially similar cross-validation procedures are presented. (12 ref) (PsycINFO Database Record (c) 2006 APA, all rights reserved).

Original languageEnglish (US)
Pages (from-to)728-730
Number of pages3
JournalJournal of Applied Psychology
Volume65
Issue number6
DOIs
StatePublished - Dec 1 1980
Externally publishedYes

Keywords

  • proper cross validation procedures with prediction equations, applications of raw vs standard scores

ASJC Scopus subject areas

  • Applied Psychology

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