Welcome to our comprehensive guide on performing a Two-Way Repeated Measures ANOVA using SPSS. Follow the steps, interpret the results in APA style, and explore practical examples with real-time variables.
Introduction to Two-Way Repeated Measures ANOVA
A Two-Way Repeated Measures ANOVA is used to evaluate the interaction between two independent variables on a dependent variable where the same subjects are used for all conditions. This method is particularly useful when measuring changes over time or under different conditions.
Benefits of Using Two-Way Repeated Measures ANOVA
This test helps in understanding the interaction effects between factors and controls for subject variability, providing more statistical power with fewer subjects. It is ideal for experiments where each subject participates in multiple conditions.
Preparing Your Data
Ensure your dataset is correctly formatted in SPSS with the repeated measures variables properly defined. For this example, we’ll use a dataset that tracks performance scores under different conditions and time points.
Steps to Perform Two-Way Repeated Measures ANOVA in SPSS
- Open SPSS and load your dataset.
- Navigate to Analyze -> General Linear Model -> Repeated Measures.
- In the Repeated Measures Define Factor(s) dialog box, define the within-subjects factors and the levels for each factor. For example, “Time” with levels “1”, “2”, and “3”, and “Condition” with levels “A” and “B”.
- Click on Define.
- In the Repeated Measures dialog box, move the appropriate variables into the Within-Subjects Variables box.
- Click OK to run the analysis.
Interpreting the Output
The output includes several tables, but the most critical ones are the Tests of Within-Subjects Effects and Tests of Between-Subjects Effects. These tables will help you determine if there are significant interaction effects.
| Source | Type III Sum of Squares | df | Mean Square | F | Sig. |
|---|---|---|---|---|---|
| Condition | 120.456 | 1 | 120.456 | 12.34 | 0.001 |
| Time | 98.765 | 2 | 49.383 | 10.21 | 0.003 |
| Condition * Time | 45.678 | 2 | 22.839 | 5.67 | 0.025 |
APA Style Interpretation
The analysis revealed a significant main effect for condition, F(1, N) = 12.34, p = 0.001, and time, F(2, N) = 10.21, p = 0.003. Additionally, there was a significant interaction effect between condition and time, F(2, N) = 5.67, p = 0.025.
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- Using SPSS for Data Analysis
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- Friedman Test
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- Pearson’s Correlation
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