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13.2. Assume that we are interested in the effects of client-therapist ethnic/
racial match on client service satisfaction. Factor A , the between-subjects
factor, is ethnic/racial match ( a 1
no match). Factor B ,
the within-subjects factor, consists of the first four treatment sessions. The
dependent variable, service satisfaction, was a single question that n
=
match and a 2
=
5
participants rated each session on, using a 1 = poor to 10 = excellent rating
of client perceived satisfaction with service. The data are as follows:
a 1 a 2
Subject b 1 b 2 b 3 b 4 Subject b 1 b 2 b 3 b 4
s 1 5 6 7 8 s 6 2 2 4 5
s 2 5 8 9 10 s 7 3 6 7 8
s 3 6 7 8 9 s 8 4 4 4 5
s 4 7 7 8 8 s 9 5 5 6 6
s 5 9 9 9 10 s 10 5 6 7 8
a. Conduct an ANOVA on these data by hand and with SPSS or SAS.
b. If the interaction is statistically significant, conduct simple effects
analyses and multiple comparisons tests by hand and with SPSS or
SAS.
13.3. Consider the following hypothetical 3
=
3 factorial data set. Factor A
is the between-subjects factor and Factor B is the within-subjects factor.
a 1
×
a 2
a 3
Subject b 1
b 2
b 3
Subject b 1 b 2 b 3
Subject b 1
b 2
b 3
s 1
5 0 5
s 6
203
s 11
789
s 2
68 2 s 7
512
s 12
91011
s 3
7 4 8
s 8
463
s 13
14
15
16
s 4
66 2 s 9
267
s 14
17
18
19
s 5
9 0 1
s 10
442
s 15
15
20
20
a.
Conduct an ANOVA on these data by hand and with SPSS or SAS.
b.
If the interaction is statistically significant, conduct simple effects
analyses and multiple comparisons tests by hand and with SPSS or
SAS.
 
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