Analyzing a Factorial ANOVA: Significant interaction Rick Balkin, - - PowerPoint PPT Presentation
Analyzing a Factorial ANOVA: Significant interaction Rick Balkin, Ph.D., LPC-S, NCC Department of Counseling Texas A&M University-Commerce Rick_balkin@tamu-commerce.edu Balkin, R. S. (2008) 1 Analyzing a Factorial ANOVA: Non-significant
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3. Report main effects for each IV 4. Compute Cohen’s f for each IV 5. Perform post hoc and Cohen’s d if necessary. 3. Plot the interaction 4. Analyze simple effects 5. Compute Cohen’s f for each simple effect 6. Perform post hoc and Cohen’s d if necessary.
Non-significant interaction Significant interaction
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Kolmogorov -Smirnov(a) Shapiro-Wilk Gender Statistic df Sig. Statistic df Sig. Men .137 30 .155 .968 30 .487 Change in GPA Women .158 30 .053 .921 30 .029
Kolmogorov -Smirnov(a) Shapiro -Wilk Note -Taking methods Statistic df Sig. Statistic df Sig. Method 1 .126 20 .200(*) .916 20 .081 Method 2 .154 20 .200(*) .971 20 .766 Change in GPA Control .144 20 .200(*) .952 20 .392
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Levene's Test of Equality of Error Variances(a) Dependent Variable: Change in GPA F df1 df2 Sig. .575 5 54 .719 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a Design: Intercept+gender+method +gender * method
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Tests of Between -Subjects Effects Dependent Variable: Change in GPA Source Type III Sum
df Mean Square F Sig. Partial Eta Squared Corrected Model 1.889(a) 5 .378 11.463 .000 .515 Intercept 4.931 1 4.931 149.582 .000 .735 gender .020 1 .020 .612 .438 .011 method 1.174 2 .587 17.809 .000 .397 gender * method .695 2 .348 10.543 .000 .281 Error 1.780 54 .033 Total 8.600 60 Corrected Total 3.669 59 a R Squared = .515 (Adjusted R Squared = .470)
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UNIANOVA gpaimpr BY gender method /emmeans=table(gender*method) comp(method).
Univariate Tests Dependent Variable: Change in GPA Gender Sum of Squares df Mean Square F Sig. Contrast .165 2 .082 2.498 .092 Men Error 1.780 54 .033 Contrast 1.705 2 .852 25.855 .000 Women Error 1.780 54 .033 Each F tests the simple effects of Note
based on the linearly independent pairwise comparisons amo ng the estimated marginal means.
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Descriptive Statistics Dependent Variable: Change in GPA Gender Note -Taking methods Mean
N Method 1 .3350 .22858 10 Method 2 .3050 .19214 10 Control .1650 .14916 10 Men Total .2683 .20064 30 Method 1 .1700 .18288 10 Method 2 .6400 .17764 10 Control .1050 .14615 10 Women Total .3050 .29254 30 Method 1 .2525 .21853 20 Method 2 .4725 .24893 20 Control .1350 .14699 20 Total Total .2867 .24938 60
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Descriptive Statistics Dependent Variable: Change in GPA Gender Note -Taking methods Mean
N Method 1 .3350 .22858 10 Method 2 .3050 .19214 10 Control .1650 .14916 10 Men Total .2683 .20064 30 Method 1 .1700 .18288 10 Method 2 .6400 .17764 10 Control .1050 .14615 10 Women Total .3050 .29254 30 Method 1 .2525 .21853 20 Method 2 .4725 .24893 20 Control .1350 .14699 20 Total Total .2867 .24938 60
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Gender (I) Note- Taking methods (J) Note- Taking methods Mean Difference (I-J)
Sig.(a) Men Method 1 Method 2 0.03 0.081 0.71 Control .170(*) 0.081 0.04 Method 2 Method 1
0.081 0.71 Control 0.14 0.081 0.09 Control Method 1
0.081 0.04 Method 2
0.081 0.09 Women Method 1 Method 2
0.081 0.00 Control 0.065 0.081 0.43 Method 2 Method 1 .470(*) 0.081 0.00 Control .535(*) 0.081 0.00 Control Method 1
0.081 0.43 Method 2
0.081 0.00