The recommendation is that when the Levene’s test is significant (indicating a violation of the assumption of homogeneity of variance), then use Brown & Forsythe’s test and if this is also significant, then accept and report the results of the latter. The Bartlett’s test of homogeneity of variance has largely been replaced by the Levene Homogeneity of variance test. Follow these steps to perform the homogeneity of variance test: Select Analyze -> Compare Means -> One-Way ANOVA…. Transfer score [number of words recalled] to Dependent List:. Transfer Group Membership [group] to Factor. Click on Options and select Homogeneity of variance test. Click Continue and click OK. Figure 1 – Brown-Forsythe F* test for Example 1. We start by running the Anova: Single Factor data analysis on the data in the range A3:D11 in Figure 3 of Basic Concepts for ANOVA. The result is shown on the left side of Figure 1. We then add the total sample size (cell G11) using the formula =SUM (G7:G10). We next build the two tables on the Testing differences in variance between groups. I have a hypothesis that a particular intervention/treatment will cause more variation in participant responses to a particular question. The intervention variable is categorical, with five different treatment groups. The response variable (the participant responses to a question) is a continuous Levene's Test: if homogeneity of variance can't be assumed for one (or more) dependent variables, then use an alpha level stricter than .05 (ie: use .001) when you evaluate the univariate ANOVAs. Introduction. Homogeneity of variance ( homoscedasticity) is an important assumption shared by many parametric statistical methods. This assumption requires that the variance within each population be equal for all populations (two or more, depending on the method). For example, this assumption is used in the two-sample t -test and ANOVA. In statistics, a mixed-design analysis of variance model, also known as a split-plot ANOVA, is used to test for differences between two or more independent groups whilst subjecting participants to repeated measures. Thus, in a mixed-design ANOVA model, one factor (a fixed effects factor) is a between-subjects variable and the other (a random We attempted to run everything in triplicate so 3 of the treatment groups are triplicated. 1 treatment group is duplicated, and 1 group is the control (single). The weights of fish are tanks averages. The largest difference is a total of 22 grams, the smallest is a difference of less than 1 between tanks. anova. levenes-test. OOyXs.