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Concept
Levene's test
Summary
In statistics, Levene's test is an inferential statistic used to assess the equality of variances for a variable calculated for two or more groups. Some common statistical procedures assume that variances of the populations from which different samples are drawn are equal. Levene's test assesses this assumption. It tests the null hypothesis that the population variances are equal (called homogeneity of variance or homoscedasticity). If the resulting p-value of Levene's test is less than some significance level (typically 0.05), the obtained differences in sample variances are unlikely to have occurred based on random sampling from a population with equal variances. Thus, the null hypothesis of equal variances is rejected and it is concluded that there is a difference between the variances in the population.
Some of the procedures typically assuming homoscedasticity, for which one can use Levene's tests, include analysis of variance and t-tests.
Levene's test is sometimes used before a comparison of means, informing the decision on whether to use a pooled t-test or the Welch's t-test. However, it was shown that such a two-step procedure may markedly inflate the type 1 error obtained with the t-tests and thus should not be done in the first place. Instead, the choice of pooled or Welch's test should be made a priori based on the study design.
Levene's test may also be used as a main test for answering a stand-alone question of whether two sub-samples in a given population have equal or different variances.
Levene's test was developed by and named after American statistician and geneticist Howard Levene.
Levene's test is equivalent to a 1-way between-groups analysis of variance (ANOVA) with the dependent variable being the absolute value of the difference between a score and the mean of the group to which the score belongs (shown below as ).
Official source
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