Cross-Validation: A Method Every Psychologist Should Know

Cross-validation is a statistical procedure that every psychologist should know. Most are possibly familiar with the procedure in a global way but have not used it for the analysis of their own data. We introduce cross-validation for the purpose of model selection in a general sense, as well as an R...

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Bibliographic Details
Published inAdvances in methods and practices in psychological science Vol. 3; no. 2; pp. 248 - 263
Main Authors de Rooij, Mark, Weeda, Wouter
Format Journal Article
LanguageEnglish
Published Los Angeles, CA SAGE Publications 01.06.2020
Subjects
predictive accuracy
prediction
p values
cross-validation
reproducibility
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Summary:Cross-validation is a statistical procedure that every psychologist should know. Most are possibly familiar with the procedure in a global way but have not used it for the analysis of their own data. We introduce cross-validation for the purpose of model selection in a general sense, as well as an R package we have developed for this kind of analysis, and we present examples illustrating the use of this package for types of research problems that are often encountered in the social sciences. Cross-validation can be an easy-to-use alternative to null-hypothesis testing, and it has the benefit that it does not make as many assumptions.
ISSN:2515-2459
2515-2467
DOI:10.1177/2515245919898466