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.
Original language | English |
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Pages (from-to) | 92-101 |
Number of pages | 10 |
Journal | International Review of Social Psychology |
Volume | 30 |
Issue number | 1 |
DOIs | |
Publication status | Published - 5 Apr 2017 |
Keywords
- Homogeneity of variance
- Homoscedasticity
- Levene's test
- Statistical power
- Student's t-Test
- Type 1 error
- Type 2 error
- Welch's t-Test
- type 2 error
- Student's t-test
- statistical power
- Welch's t-test
- type 1 error
- homogeneity of variance