To analyze a split-plot design using SPSS, you first need to structure your data to include the main plot and subplot factors along with the dependent variable. Then, you can conduct a Mixed ANOVA by going to Analyze > General Linear Model > Mixed in SPSS, where you’ll specify your fixed and random factors and the dependent variable.
It is important to ensure that your data meets the assumptions of normality, homogeneity of variances, and sphericity. After running the analysis, you should interpret the main effects, interaction effects, and any post hoc tests to understand how your factors influence the dependent variable. For detailed guidance, you can search for online tutorials that demonstrate the process in SPSS. You can start from here:
https://www.smartstat.info/en/tutorial/spss/tutorial-spss-rancangan-split-plot.html
To analyze a split-plot design in SPSS, start by organizing your data, ensuring you have columns for the dependent variable, between-subjects factors, and within-subjects factors. Open SPSS and load your dataset, then go to the Analyze menu, select General Linear Model, and choose Repeated Measures. Define your within-subjects factor by naming it (like "Time") and specifying the number of levels (e.g., three time points), then assign your within-subjects variables (e.g., measurements at different time points). Move your between-subjects factor (e.g., "Group") to the appropriate box. Specify the model, create interaction plots if desired, and choose additional options like descriptive statistics or effect size. Run the analysis by clicking OK, and SPSS will produce tables showing means, standard deviations, and significance tests for the effects and interactions of both within- and between-subjects factors. Interpret these results to understand how the factors influence your dependent variable.
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