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Now, after the word COMPARE, type drug enclosed in parentheses: The subcommand /EMMEANS = TABLES(drug*sex) is the one we need to modify we need to specify the factor for which we want pairwise comparisons.Ĭopy COMPARE ADJ(LSD) from the subcommand /EMMEANS = TABLES(drug), and paste it after the interaction, so: /EMMEANS = TABLES(drug*sex) COMPARE ADJ(LSD). This will open a Syntax window, where you should find something like this: Now click the Continue button to return to the Univariate dialog box. This leaves a choice between SIDAK or none.) Note that since Bonferroni simply multiplies by the number of comparisons, it will be excessively conservative for most situations which require simple effects. (Leave this as LSD(none) if you don't have a preference. Choose the interaction(s) for which you wish to request Simple Effects, and click the triangle button to add them to the list "Display Means for:".Įven if you are not interested in any of the main effects, for convenience add one of the main effects, place a check in the box labeled "Compare main effects", and choose your preferred option for "Confidence interval adjustment". In the box labeled "Estimated Marginal Means", you should see a list of "Factors and Factor Interactions". (If not, set up the model at this time.) Click on the Options. Assuming that you just ran your ANOVA model and observed the significant interaction in the output, the dialog will have the dependent variables and factors already set up. Return to the General Linear Model->Univariate dialog.
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Here, we will describe how to make the necessary modifications to syntax pasted from the General Linear Model->Univariate dialog box. Unfortunately, at this time to obtain a Simple Effects Test does require the use of SPSS command syntax. This test can be performed with SPSS General Linear Model, using the Estimated Marginal Means option. (For multi-way analyses, all combinations of levels of the other factors.) Sometimes these are referred to as Simple Main Effects. Simple Effects tests reveal the degree to which one factor is differentially effective at each level of a second factor. This will produce a table comparing all pairs of levels of one factor, for each level of all the other factors.