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Cell means for
all conditions.
Least Squares Means
Standard
Error
Effect
gender
gender
color
color
toytype
toytype
gender color
gender color
gender color
gender color
gender toytype
gender toytype
gender toytype
gender toytype
color toytype
color toytype
color toytype
color toytype
gender color toytype
gender color toytype
gender color toytype
gender color toytype
gender color toytype
gender color toytype
gender color toytype
gender color toytype
DF
t Value Pr > t
gender color toytype
Estimate
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8.37
11.24
13.60
8.06
10.43
11.24
9.83
3.24
9.41
8.16
4.29
8.78
10.46
7.11
10.31
10.09
5.32
6.76
4.86
9.88
1.57
3.29
9.72
4.39
5.96
6.27
< .0001
< .0001
< .0001
<
1
2
6.2500
8.4000
9.2000
5.4500
7.0500
7.6000
9.4000
3.1000
9.0000
7.8000
4.1000
8.4000
10.0000
6.8000
9.3000
9.1000
4.8000
6.1000
6.2000
12.6000
2.0000
4.2000
12.4000
5.6000
7.6000
8.0000
0.7471
0.7471
0.6762
0.6762
0.6762
0.6762
0.9563
0.9563
0.9563
0.9563
0.9563
0.9563
0.9563
0.9563
0.9021
0.9021
0.9021
0.9021
1.2757
1.2757
1.2757
1.2757
1.2757
1.2757
1.2757
1.2757
1
2
.0001
< .0001
< .0001
<
1
2
.0001
0.0119
< .0001
<
1
1
2
2
1
1
2
2
1
2
1
2
.0001
0.0027
< .0001
< .0001
0.001
< .0001
< .0001
0.0007
0.0001
0.0013
< .0001
0.1556
0.0110
< .0001
0.0023
0.0003
0.0002
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
1
2
2
1
1
2
2
1
1
2
2
1
1
1
1
2
2
2
2
Figure 15.29
The least squares means for all of the effects.
15.11 OUTPUT FOR THE POST-ANOVA ANALYSIS IN SAS
A portion of the results of the simple effects tests are shown in Figures
15.32 and 15.33. The conditions being compared are read in a manner
analogous to how we described this process in the earlier chapters. To
illustrate this, consider, for example, the eleventh comparison in the tables.
The first three coded columns represent one condition and the last three
coded columns represent the other condition. We are thus comparing
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