How should one apply Levene's Test when testing the difference in means between two groups for a large number of variables.
The data consists of replies from two groups of respondents (n=66 and n=21, respectively). All respondents have answered a large number of questions (a battery of 40 similar questions, most of them on a 7-step Likert scale). Now I want to examine whether the two groups are significantly different in their replies.
To do this, I have used the 'Independent-Samples T-test'. For each of the 15 variables SPSS gives me one significance for 'Equal variances assumed' and another significance for 'Equal variances not assumed'. Had I done this test for a single variable only, it would have been straight forward: I would simply have used Levene's Test to determine which of the two assumptions to go with. However, since I have 40 variables to test I am not sure what the correct procedure would be:
a) Should I apply Levene's test independently for each variable and thus use the 'Equal variances assumed' value for some variables and the 'Equal variances not assumed' for others? (The questions are all of the same type, so there is no a priori reason why variances should be equal for some questions but not for others.)
b) Or should I draw the conclusion that since equal variances can not be assumed for SOME of the variables, I should not assume it for ANY of the variables, and thus consistently use the 'Equal variances not assumed' values for all variables?
I am grateful for any guidance you can suggest.
Göran Lindqvist PhD candidate Stockholm School of Economics