If there is a research model with one IV, one DV and one continuous moderator. So, how to check the parametric assumptions in SPSS?
Include an Interaction Term:
Create an interaction term by multiplying the IV and the moderator.
Run the Moderated Regression Analysis:
Set up a regression model where the DV is the outcome variable, and the IV, moderator, and interaction term are the predictors.
Check Parametric Assumptions for the Model
First, use the Shapiro-Wilk test, Q-Q plots, or histograms to determine whether the residuals are normal. Examine scatter plots for the correlations between the IV, moderator, and DV to confirm linearity. To verify constant variance, plot residuals against anticipated values to check for homoscedasticity. Use Variance Inflation Factor (VIF) numbers to assess multicollinearity; values more than 10 suggest issues. Additionally, use the Durbin-Watson statistic to verify the independence of mistakes; a value near 2 is desired. Lastly, center the continuous variables before constructing the interaction term to prevent multicollinearity and enhance model interpretability. These verifications guarantee that the data satisfies the presumptions required for a reliable regression analysis.
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