par Delacre, Marie ;Lakens, Daniel;Leys, Christophe
Référence International Review of Social Psychology, 30, 1, page (92-101)
Publication Publié, 2017
Article révisé par les pairs
Résumé : 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.