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Chapter 14. Follow-up Tests for the Two-Way Factorial ANOVA



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Simple Tricks for Using SPSS for Windows Chapter 14 Follow up Tests for the Two Way Factorial ANOVA The Interaction is Not Significant If you have performed a two way ANOVA using the General Linear Model Univariate choice from the Analyze menu and the interaction is not statistically significant but one of the main effects is significant and has more than two levels it is easy to perform pairwise comparisons among the marginal means of the significant main effect Just return to the Univariate dialog box and click on Post Hoc When the Post Hoc box opens you will see your two factors listed on the left move the factor you want to test further or if applicable both of them to the right Next choose the post hoc procedure that you prefer you will have the same choices that are available from the Post Hoc box of Compare Means One Way ANOVA including methods like Games Howell that are based on separate variance tests and perform the analysis You will get the output for the twoway ANOVA again but this time Post Hoc tests on your selected factor s will appear If the interaction is significant it may still make sense e g the interaction is ordinal to follow up on significant main effects However you may also want to test the simple main effects i e one way ANOVAs for one of the factors conducted separately at each level of the other factor This is also easy to do in SPSS for Windows but that fact is certainly not obvious from the menu selections or the Help topics I would not have known about the syntax shortcut I describe below had I not seen it in the helpful data analysis guide by Weinberg and Abramowitz 2002 Bear in mind that even if the interaction falls a bit short of significance at the conventional 05 level it may be reasonable to analyze the simple main effects anyway especially if your pattern of cell means is consistent with your hypotheses and expectations Testing Simple Main Effects There are actually several methods for testing simple main effects in SPSS for



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