Select Analyze, then General Linear Model, then Repeated Measures (see Figure 9-2).įigure 9-2 Preparing for the Mixed Factorial Analysis You must first specify repeated measures to identify the within-subjects variable(s), and then specify the between-groups factor(s). The initial steps are identical to those in the within-subjects ANOVA. To conduct this analysis, you will use the repeated measures procedure.
#Factorial anova spss download#
You may optionally download a copy of the data file.įigure 9-1 SPSS data structure for mixed factorial design Performing the Mixed Factorial Anova The data appropriately entered in SPSS should look something like the following (see Figure 9-1). As always it is helpful to include a column for participant (or case) number.
There will be a column for the participants' age, which is the between-groups variable, and three columns for the repeated measures, which are the distraction conditions. Note that there are eight separate participants, so the data file will require eight rows. The scores on the data sheet below represent the number of words recalled out of ten under each distraction condition. This is a 2 (age) x 3 (distraction condition) mixed factorial design. To do this, you obtained a group of younger adults and a separate group of older adults and had them learn under three conditions (eyes closed, eyes open looking at a blank field, eyes open looking at a distracting field of pictures). Example DataĪs an example, assume that you conducted an experiment in which you were interested in the extent to which visual distraction affects younger and older people's learning and remembering. The between-groups factor would need to be coded in a single column as with the independent-samples t test or the one-way ANOVA, while the repeated measures variable would comprise as many columns as there are measures as in the paired-samples t test or the repeated-measures ANOVA. In the simplest case, there will be one between-groups factor and one within-subjects factor.
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