Should I use a dependent samples t-test or repeated measures ANOVA?
For students learning about statistics, some ask whether they should use an dependent samples t-test (also called a paired samples t-test) or a repeated-measures ANOVA. Let’s start at the beginning. Both of these tests assess differences across the same observations (or pairs) on scale level variables. For example, is there a difference in GPA at time 1 and GPA at time 2, or is there partner agreement on Extraversion, etc.
Assumptions
Both the dependent samples t-test and the repeated measures ANOVA have the same assumptions: normality and homogeneity of variance. You can assess the normality assumptions with a Shapiro-Wilk test or a Q-Q scatterplot. You can assess the homogeneity of variance with Levene’s test. A non-significant result in the Shapiro and Levene tests indicates that the paired sample t-test or repeated measures ANOVA assumptions are met.
So which one should I use?
For a test at two time points or with paired samples, the t-value and F-value are equivalent. If the probability is ≤ 0.05, the means differ.
Caveat
Use repeated measures ANOVA for three or more time points or values. The t-test only works with two.
Try www.IntellectusStatistics.com free for a week, download a dataset, and run both tests.
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