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• Spss 22 tutorial ppt how to#

Spss 22 tutorial ppt how to#

For our purposes, it doesn’t matter too much what this means, we just need to know how to figure out whether the requirement has been satisfied. Assumption of SphericityĪ requirement that must be met before you can trust the p-value generated by the standard repeated-measures ANOVA is the homogeneity-of-variance-of-differences (or sphericity) assumption. Of course, we won’t know whether these differences in the means reach significance until we look at the result of the ANOVA test. In our example, it seems as if fear of spiders increases over time, with the greatest increase (20.90 to 22.26 on the SPQ scale) occurring between year 1 (SPQ_Time2) and year 2 (SPQ_Time3). The comparison between means (see above) gives us an idea of the direction of any possible effect. The descriptive statistics that SPSS outputs are easy enough to understand. (In future tutorials, we’ll look at some of the more complex options available to you, including multivariate tests and polynomial contrasts). For the purposes of this tutorial, we’re going to concentrate on a fairly simple interpretation of all this output. SPSS produces a lot of output for the one-way repeated-measures ANOVA test.

All you’ve got to do is hit OK, and you’ll see the result pop up in the Output Viewer. You should be looking at the original Repeated Measures dialog box. Hit the Continue button(s) once you’ve got this set up. And then in the Estimated Marginal Means section (or dialog box if you’re using the current version of SPSS), move “time” over to the Display Means for box, and then tick Compare main effects, and choose Bonferroni as the Confidence interval adjustment option. You want to display descriptive statistics and estimates of effect size, so tick these options in the Display section (as above). It’s not too difficult to get the options sorted out.

If you’re not, then you need to click on the EM Means button (in the Repeated Measures dialog box) after you’ve finished with the Options dialog box, and set up the estimated marginal means there. We’re going to assume that you’re using a previous version of SPSS, and you’re seeing the estimated marginal means option. Previous versions include an option for specifying estimated marginal means. The most recent version of SPSS (26) has an options dialog box that looks like this. What you see here depends on the version of SPSS you’re using. We’re now ready to set up some of the options for the repeated-measures ANOVA. The dialog box should look something like this once you’ve completed this stage. In our case, it just means moving SPQ_Time1, SPQ_Time2 & SPQ_Time3 into the three slots on the right. You can drag and drop, or use the arrow button in the middle of the box. You’ve got to shift your within-subjects variables over to the Within-Subjects Variables box ensuring you maintain the correct order. Click on the Define button, which will bring up the Repeated Measures dialog blox. Okay, it’s now time to set up the within-subjects variables (at the moment SPSS knows that our within-subjects factor has three levels, but it doesn’t know which of our variables corresponds to each level). The dialog box should now look like this. And we have 3 levels, so input 3 into Number of Levels. This will bring up the Repeated Measures Define Factor(s) dialog box.Īs we noted above, our within-subjects factor is time, so type “time” in the Within-Subject Factor Name box. To start, click Analyze -> General Linear Model -> Repeated Measures. This is what we’ll test with a one-way repeated-measures ANOVA. The null hypothesis is that the mean SPQ score is the same for all levels of the within-subjects factor. The independent variable – or, to adopt the terminology of ANOVA, the within-subjects factor – is time, and it has three levels: SPQ_Time1 is the time of the first SPQ assessment SPQ_Time2 is one year later and SPQ_Time3 two years later. The average score for a person with a spider phobia is 23, which compares to a score of slightly under 3 for a non-phobic. The variable we’re interested in here is SPQ which is a measure of the fear of spiders that runs from 0 to 31. This is the data from our “study” as it appears in the SPSS Data View. Press the OK button, and your result will pop up in the Output Viewer