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These are the probabilities
of the differences occurring
by chance alone for the
pairwise comparisons with
reside as the first order.
Pairwise Comparisons
Dependent Variable: range 0-60
95% Confidence Interval for
Difference a
Mean
Difference
(I-J)
Sig a
(I) gender
(J) gender
city reside size
large
Std. Error
Lower Bound
Upper Bound
female
male
-1.000
3.838
.797
-8.922
6.922
female
male
1.000
3.838
.797
-6.922
8.922
small
female
male
male
10.000 *
3.838
.016
2.078
17.922
female
-10.000 *
3.838
.016
-17.922
-2.078
male
32.000 *
rural
female
male
3.838
.000
24.078
39.922
-32.000 *
female
3.838
.000
-39.922
-24.078
Based on estimated marginal means
*. The mean difference is significant at the .05 level.
a. Adjustment for multiple comparisons: Bonferroni.
Figure 8.17
Simple effects comparisons of gender for each level of reside .
8.12 SPSS OUTPUT FOR THE POST-ANOVA ANALYSES
8.12.1 SIMPLE EFFECTS ANALYSES: GENDER
Figure 8.17 shows the Pairwise Comparisons for the first simple effects
analysis in which we asked SPSS to compare males and females at each
level of reside . There are three main horizontal rows in the Pairwise
Comparisons table, the first for large , the next for small , and the last for
rural . Each is divided into two portions but with the same information
provided for each of those portions. Reading across the very top row, for
those living in large cities, the female loneliness mean (15.00) minus the
male loneliness mean (16.00) is
1.00. That difference is not statistically
= .
significant ( p
797).
Consider the next major row. For those residing in small towns, the
difference between the female mean (38.00) and the male mean (28.00) is
10.00, a difference that is statistically significant ( p
016). We can also
see that the female-male difference is significant for those residing in rural
communities.
= .
8.12.2 SIMPLE EFFECTS ANALYSES: RESIDE
Figure 8.18 shows the PairwiseComparisons for the second simple effects
analysis in which we asked SPSS to compare the places of residence at each
level of gender . There are two main horizontal rows in this output, one
for females and another for males . Each is divided into three portions
corresponding to the three levels of reside .
Let's examine the first division of the first row of the table. We are
working with the loneliness scores of females. The first comparison is
between those living in large cities and those living in small towns. The
difference between these means (large
small) is
23.00, a difference that
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