Cross-Validation: A Method Every Psychologist Should Know

Abstract

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.