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SPSS Statistics

Example

A researcher wants to understand how exercise might reduce heart disease. The researcher wants to concentrate on a protein called C-Reactive Protein (CRP), which is a marker of chronic inflammation in the body and associated with heart disease: the greater the concentration of CRP, the greater the risk of heart disease. Regular exercise reduces the risk of heart disease. Therefore, the researcher would like to know whether exercise has an effect on CRP concentration because this might indicate that exercise has an anti-inflammatory effect.

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To test out this theory, the researcher recruits 10 subjects to undergo a 6-month exercise-training programme. CRP concentration is measured at three different stages within the 6-month exercise-training programme: (1) pre-intervention (i.e., pre); (2) midway through the intervention at 3 months (i.e., mid); and (3) immediately post-intervention (i.e., post). These three time points reflect the three levels of our within-subjects factor, time (i.e., a within-subjects factor that is measured on an ordinal scale, although a within-subjects factor can also be measured on a nominal scale when carrying out a one-way repeated measures ANOVA). The dependent variable is CRP, which is measured in mg/L (i.e., a dependent variable that is measured on a continuous scale).

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The CRP concentrations pre-intervention were recorded in the crp_pre variable, the CRP concentrations midway through the intervention in the crp_mid variable and the post-intervention CRP concentrations in the crp_post variable. The researcher would like to know whether there are changes in CRP concentration over time. In variable terms, the researcher would like to know if there are differences between the three variables: crp_pre, crp_mid and crp_post.

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In our enhanced repeated measures ANOVA guide, we show you how to correctly enter data in SPSS Statistics to run a repeated measures ANOVA. You can learn about our enhanced data setup content on our Features: Data Setup page. Alternatively, see our generic, “quick start” guide: Entering Data in SPSS Statistics.

SPSS Statistics

Test Procedure in SPSS Statistics

The General Linear Model > Repeated Measures… procedure below shows you how to analyse your data using a repeated measures ANOVA in SPSS Statistics when the five assumptions in the previous section, Assumptions, have not been violated. At the end of these 13 steps, we show you how to interpret the results from this test. If you are looking for help to make sure your data meets assumptions #3, #4 and #5, which are required when using a repeated measures ANOVA and can be tested using SPSS Statistics, you can learn more in our enhanced guides (see our Features: Overview page to learn more).

Since some of the options in the General Linear Model > Repeated Measures… procedure changed in SPSS Statistics version 25, we show how to carry out a repeated measures ANOVA depending on whether you have SPSS Statistics versions 25, 26, 27 or 28 (or the subscription version of SPSS Statistics) or version 24 or an earlier version of SPSS Statistics. The latest versions of SPSS Statistics are version 28 and the subscription version. If you are unsure which version of SPSS Statistics you are using, see our guide: Identifying your version of SPSS Statistics.

SPSS Statistics versions 25, 26, 27 and 28 (and the subscription version of SPSS Statistics)

Click Analyze > General Linear Model > Repeated measures… on the top menu, as shown below:
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Note: In version 27 and the subscription version, SPSS Statistics introduced a new look to their interface called “SPSS Light“, replacing the previous look for versions 26 and earlier versions, which was called “SPSS Standard“. Therefore, if you have SPSS Statistics versions 27 or 28 (or the subscription version of SPSS Statistics), the images that follow will be light grey rather than blue. However, the procedure is identical.

You will be presented with the Repeated Measures Define Factor(s) dialogue box, as shown below:

Explanation: This dialogue box is where you inform SPSS Statistics that the three variables – crp_pre, crp_mid and crp_post – are three levels of the within-subjects factor, time. Without doing this, SPSS Statistics will think that the three variables are just that, three separate variables.
In the Within-Subject Factor Name: box, replace “factor1” with a more meaningful name for your within-subjects factor. For example, we replaced “factor1” with “time” because this is the name of our within-subjects factor (i.e., time). Next, enter the number of levels of your within-subjects factor into the Number of Levels: box. For example, our within-subjects factor, time, has three levels, representing the three time points when our dependent variable, CRP, was measured (i.e., pre-intervention, crp_pre, mid-intervention, crp_mid, and post-intervention, crp_post). Therefore, we entered “3” into the Number of Levels: box, as shown below: Click on the button and you will be presented with the following screen:
In the Measure Name: box, enter a name that reflects the name of your dependent variable. Since our dependent variable is CRP, we entered “CRP“, as shown below: Click on the button and you will get the following screen:
Click on the button and you will be presented with the Repeated Measures dialogue box, as shown below:
Transfer crp_pre, crp_mid and crp_post into the “_?_(1,CRP)“, “_?_(2,CRP)” and “_?_(3,CRP)” placeholders respectively in the Within-Subjects Variables (time): box, by highlighting all the variables in the left-hand box (by clicking on them whilst holding down the shift-key), and then clicking on the top button. You will end up with the following screen:
Click on the button. You will be presented with the Repeated Measures: Profile Plots dialogue box, as shown below:
Transfer the within-subjects factor, time, from the Factors: box into the Horizontal Axis: box by clicking on the top button. You will end up with the following screen:
Click on the button. This will transfer “time” from the Horizontal Axis: box to the Plots: box, as shown below:
Click on the button and you will be returned to the Repeated Measures dialogue box.
Click on the button and you will be presented with the Repeated Measures: Estimated Margin Means dialogue box, as shown below:
Transfer time from the Factor(s) and Factor Interactions: box to the Display Means for: box using the button. This will activate the Compare main effects checkbox (i.e., it will no longer be greyed out). Tick this checkbox and select from the drop-down menu under Confidence interval adjustment:. You will be presented with the following screen:
Click on the button and you will be returned to the Repeated Measures dialogue box.
Click on the button and you will be presented with the Repeated Measures: Options dialogue box, as shown below:
In the -Display- area, tick the Descriptive statistics and Estimates of effect size checkboxes. You will be presented with the following screen:
Click on the button and you will be returned to the Repeated Measures dialogue box.
Click on the button. This will generate the output.

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After running the 16-step procedure above, you will have generated the results for a repeated measures ANOVA with a post hoc test. We discuss this output on the next page. You can ignore the first section on the next page, which shows how to carry out a one-way repeated measures ANOVA with a post hoc test when you have SPSS Statistics version 24 or an earlier version of SPSS Statistics.

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