SOLUTION: Using the SPSS Output given below, interpret the data in the table for the within-subjects effect, the between-subjects effect, and the interaction.
Make sure to discuss t
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-> SOLUTION: Using the SPSS Output given below, interpret the data in the table for the within-subjects effect, the between-subjects effect, and the interaction.
Make sure to discuss t
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Question 725905: Using the SPSS Output given below, interpret the data in the table for the within-subjects effect, the between-subjects effect, and the interaction.
Make sure to discuss the findings of the analysis in terms of what they actually mean in the context of the study (your final project for this lab).
Within-Subjects Factors
Measure:MEASURE_1
Anxiety_Level
Dependent Variable
1
RCMAS_Pretreatment
2
RCMAS_Posttreatment
Between-Subjects Factors
Value Label
N
Treatment_Condition
1
CBT
33
2
PSY
33
3
SUPP
33
Descriptive Statistics
Treatment Condition
Mean
Std. Deviation
N
RCMAS_Pretreatment
CBT
20.3333
3.70529
33
PSY
19.9091
3.22455
33
SUPP
20.4242
4.30864
33
Total
20.2222
3.74045
99
RCMAS_Posttreatment
CBT
7.3939
4.34410
33
PSY
11.7879
3.79768
33
SUPP
16.0909
3.97149
33
Total
11.7576
5.36255
99
Multivariate Testsb
Effect
Value
F
Hypothesis df
Error df
Sig.
Anxiety_Level
Pillai's Trace
.809
407.585a
1.000
96.000
.000
Wilks' Lambda
.191
407.585a
1.000
96.000
.000
Hotelling's Trace
4.246
407.585a
1.000
96.000
.000
Roy's Largest Root
4.246
407.585a
1.000
96.000
.000
Anxiety_Level * Treatment_Condition
Pillai's Trace
.424
35.278a
2.000
96.000
.000
Wilks' Lambda
.576
35.278a
2.000
96.000
.000
Hotelling's Trace
.735
35.278a
2.000
96.000
.000
Roy's Largest Root
.735
35.278a
2.000
96.000
.000
a. Exact statistic
b. Design: Intercept + Treatment_Condition
Within Subjects Design: Anxiety_Level
Mauchly's Test of Sphericityb
Measure:MEASURE_1
Within Subjects Effect
Mauchly's W
Approx. Chi-Square
df
Sig.
Epsilona
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
Anxiety_Level
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 + Treatment_Condition
Within Subjects Design: Anxiety_Level
Tests of Within-Subjects Effects
Measure:MEASURE_1
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
Anxiety_Level
Sphericity Assumed
3546.687
1
3546.687
407.585
.000
Greenhouse-Geisser
3546.687
1.000
3546.687
407.585
.000
Huynh-Feldt
3546.687
1.000
3546.687
407.585
.000
Lower-bound
3546.687
1.000
3546.687
407.585
.000
Anxiety_Level * Treatment_Condition
Sphericity Assumed
613.949
2
306.975
35.278
.000
Greenhouse-Geisser
613.949
2.000
306.975
35.278
.000
Huynh-Feldt
613.949
2.000
306.975
35.278
.000
Lower-bound
613.949
2.000
306.975
35.278
.000
Error(Anxiety_Level)
Sphericity Assumed
835.364
96
8.702
Greenhouse-Geisser
835.364
96.000
8.702
Huynh-Feldt
835.364
96.000
8.702
Lower-bound
835.364
96.000
8.702
Tests of Within-Subjects Contrasts
Measure:MEASURE_1
Source
Anxiety_Level
Type III Sum of Squares
df
Mean Square
F
Sig.
Anxiety_Level
Linear
3546.687
1
3546.687
407.585
.000
Anxiety_Level * Treatment_Condition
Linear
613.949
2
306.975
35.278
.000
Error(Anxiety_Level)
Linear
835.364
96
8.702
Tests of Between-Subjects Effects
Measure:MEASURE_1
Transformed Variable:Average
Source
