International review of social psychology · 2017 · 978 citations · 41 references
Social SciencesBehavioral SciencesPsychologyExperimental DesignPsychometricsStatisticsHypothesis TestingPsychological TestingStatistical AnalysisStatistical InferenceTest BiasTest ValidityBias In Psychological TestingHomogeneity Of VarianceRobustnessT-testTest Bias AnalysisType Ii Error AnalysisVariances
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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Handbook of Parametric and Nonparametric Statistical Procedures
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