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Cross-validation: What is it and how is it used in regression?

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  • Kristi Morin
  • John L. Davis

Abstract

The purpose of this article is to explain cross-validation and describe its use in regression. Because replicability analyses are not typically employed in studies, this is a topic with which many researchers may not be familiar. As a result, researchers may not understand how to conduct cross-validation in order to evaluate the replicability of their data. This article not only explains the purpose of cross-validation, but also uses the widely available Holzinger and Swineford (1939) dataset as a heuristic example to concretely demonstrate its use. By incorporating multiple tables and examples of SPSS syntax and output, the reader is provided with additional visual examples in order to further clarify the steps involved in conducting cross-validation. A brief discussion of the limitations of cross-validation is also included. After reading this article, the reader should have a clear understanding of cross-validation, including when it is appropriate to use, and how it can be used to evaluate replicability in regression.

Suggested Citation

  • Kristi Morin & John L. Davis, 2017. "Cross-validation: What is it and how is it used in regression?," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(11), pages 5238-5251, June.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:11:p:5238-5251
    DOI: 10.1080/03610926.2015.1099672
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    Cited by:

    1. Robert Giel & Alicja Dąbrowska, 2021. "Estimating Time Spent at the Waste Collection Point by A Garbage Truck with A Multiple Regression Model," Sustainability, MDPI, vol. 13(8), pages 1-14, April.
    2. Robert Baumhof & Thomas Decker & Klaus Menrad, 2019. "A Comparative Analysis of House Owners in Need of Energy Efficiency Measures but with Different Intentions," Energies, MDPI, vol. 12(12), pages 1-19, June.

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