Why Psychologists Should by Default Use Welch’s <i>t</i>-test Instead of Student’s <i>t</i>-test

Authors

  • Marie Delacre Université Libre de Bruxelles, Service of Analysis of the Data (SAD), Bruxelles Array
  • Daniël Lakens Eindhoven University of Technology, Human Technology Interaction Group, Eindhoven Array
  • Christophe Leys Université Libre de Bruxelles, Service of Analysis of the Data (SAD), Bruxelles Array

DOI:

https://doi.org/10.5334/irsp.82

Keywords:

Welch’s t-test, Student’s t-test, homogeneity of variance, Levene’s test, Homoscedasticity, statistical power, type 1 error, type 2 error

Abstract

When comparing two independent groups, psychology researchers commonly use Student’s t-tests. Assumptions of normality and homogeneity of variance underlie this test. More often than not, when these conditions are not met, Student’s t-test can be severely biased and lead to invalid statistical inferences. Moreover, we argue that the assumption of equal variances will seldom hold in psychological research, and choosing between Student’s t-test and Welch’s t-test based on the outcomes of a test of the equality of variances often fails to provide an appropriate answer. We show that the Welch’s t-test provides a better control of Type 1 error rates when the assumption of homogeneity of variance is not met, and it loses little robustness compared to Student’s t-test when the assumptions are met. We argue that Welch’s t-test should be used as a default strategy.

 

Publisher’s Note: A correction article relating to this paper has been published and can be found at https://www.rips-irsp.com/articles/10.5334/irsp.661/.

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Published

2017-04-05