Simple Mixed Design - Analysis of Variance Designs - page 374

Box's Test of Equality of Covariance Matrices a

Box's M
F
df1
df2
Sig.

5.613
.709
6
3588.923
.643
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups.
a. Design: Intercept leadstyl

Within Subjects Design: project
Figure 13.10

+

Box's M test.

Mauchly's Test assesses equality of
group variances and correlations.
Because there is only one correlation, it
cannot be compared to any other.
Therefore, the sphericity assumption
cannot be tested. This is why there is
zero df and why there is no computed
probability (Sig.).

Mauchly's Test of Sphericity b

Measure: MEASURE_1

Epsilon a

Approx. Greenhouse

e-Geisser

Mauchly's W Chi-Square

Within Subjects Effect

df Sig. Huynh-Feldt Lower-bound

project

1.000 .000 0 . 1.000 1.000 1.000

Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is
proportional to an identity matrix.
a. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in
the Tests of Within-Subjects Effects table.
b. Design: Intercept+leadstyl
Within Subjects Design: project

Figure 13.11 Mauchly's test.

The equal variances assumption is not
violated, probabilities (Sig.) are > .05.

Levene's Test of Equality of Error Variances a

F df1 df2 Sig.

simple projects
complex project

.063 2 12 .939

1.948 2 12 .185

Tests the null hypothesis that the error variance of the dependent
variable is equal across groups.
a. Design: Intercept+leadstyl
Within Subjects Design: project

Figure 13.12 Levene's test.