So let's go ahead and get started with our problem in SPSS. Now in SPSS you can
see here we have three variables, gender, where we have males and females; I can turn
those value labels off for a minute.
We have males and females given by 1s and 2s, and we have our two dependent
variables, empathic concern and cognitive perspective taking.
So notice here we have to have at least two variables once again for MANOVA, so
you can see those here, and then we have our grouping variable which is gender. So
let's go ahead and run the MANOVA. So to do that we want to go to Analyze and
then General Linear Model and then Multivariate.
And here the Multivaraite
dialog box opens. We're going to take our two dependent variables, empathic
concern and perspective-taking, move those over to the dependent variables box, and
I just pressed and held the control key to grab both of those at once, and then
move gender to Fixed Factor(s).
And then let's go ahead and go to Options, select gender and move that over
to the Display Means for box, check on Descriptive statistics, Estimates of
effect size, and Homogeneity tests, and then click Continue and then go ahead
and click OK.
Next we get our results out, and you can see here our first table shows us our
Between-Subjects Factors,
and here we have gender, 1 and 2, 1 is male 2 is female, and notice we have 15 adolescents
in each group.
Next is our Descriptive Statistics table. We have empathic concern for males and
females, so here's these two means, and notice in the sample, let's just go ahead
and go through this and ask yourself, which of the two genders scored higher
on empathic concern? Now we don't know if this is significant yet, but
just descriptively, just visually inspecting. Notice that females scored
higher than males by 8.27 points, approximately, on empathic concern.
And then here on perspective-taking, we can see that females scored about almost
three points higher on perspective-taking than did males.
OK next we have Box's Test for Equality of Covariance Matrices. Now this test
tests an assumption of the MANOVA, which is that the variance-covariance
matrices, also referred to as the covariance matrices, as you see here,
are equal for the two groups. Now we're going to have a separate video on this
assumption to look at it in more detail, but basically in a nutshell it's very
similar to the equal variance assumption for the ANOVA; this assumption is the
multivariate generalization or extension of the assumption of equal variances for
the ANOVA. And what we have here is it grows as our groups and/or number of
dependent variables grow. And in that separate video I'm going to go into what
it's exactly testing, but in a nutshell, it's testing the corresponding
variances and covariances are equal for the two groups. But for now all you
really need to know is that we want to look at our p-value here and we hope
that this is greater than .05. But in fact this test, Box's test the
equality of covariance matrices, is so sensitive to departures from non-
normality, that a lot of people will even use a standard of p is greater than
.001. So, basically, we want this result to be not significant.
So if we use the more lenient standard and use p is greater than
.001,
then you can clearly see, well at either level (.05 or .001), this is not significant.
So that provides us some evidence that the variance-covariance matrices are
equal for the two groups. And that's an assumption of MANOVA, we want that to
hold. So, unlike our significance tests on means, we want this to be greater than
.05 or greater than .001. And in that other video I'll go
into more detail, some of the subtleties of that, and the research findings as
well, and what we can do if we do have a p-value that's less than say, .001, for
Box's test.
OK next we'll go to our Multivariate Tests box