How do I perform a repeated measures analysis of variance in SPSS?
The key thing here is that each combination of the repeated measures factors is represented by a separate column. By contrast, all the levels of a between subject factor are entered in the same column.
For example suppose we wish to compare activity in four areas of the brain - the hippocampus, area 23, areas 29 and 30 and acingulate congulate. Activity in each of these areas is entered in four columns called hippo, a23, a29 and acin respectively.
The syntax below does this by specifying a within subjects factor, region, with four levels made up of each of the four columns. You can also use the repeated measures option in the General Linear Model menu. If you use the menu interface note that you can select more than one variable at a time to define the repeated measures factor by holding the Alt and Ctrl keys down and left mouse clicking on the variables. You can also highlight adjacent variables all at once by going to the bottom of the list of variables you wish to highlight and then holding down the shift key (the up arrow between the 'Control' and 'Caps Lock' keys) and clicking on the variable at the top of the list. These approaches can be quicker than defining one variable at a time especially if you have a lot of variables.
If in addition you think that the acingulate congulate will show less activity than the other three areas you can test this using /MMATRIX subcommand. It specifies user defined contrast coefficients for each of the levels of the repeated measures factor and is only available using syntax.
filter by group. GLM hippo a23 a29 acin /WSFACTOR = region 4 Polynomial /METHOD = SSTYPE(3) /CRITERIA = ALPHA(.05) /MMATRIX "Hip_a23_a29v.acin" all -0.333 -0.333 -0.333 1 /WSDESIGN = region.
An equivalent form of the /MMATRIX subcommand above is
/MMATRIX "Hip_a23_a29v.acin" hippo -0.333 a23 -0.333 a29 -0.333 acin 1
Note the contrast coefficients sum to zero and specify a paired t-test comparing the activity means of the hippocompus, areas 23, 29/30 with that of the acingulate congulate. A slightly more cumbersome approach uses the SPSS MANOVA procedure.