How do you explain the moderation effect?

The effect of a moderating variable is characterized statistically as an interaction; that is, a categorical (e.g., sex, ethnicity, class) or quantitative (e.g., level of reward) variable that affects the direction and/or strength of the relation between dependent and independent variables.

How do you do a moderation analysis in SPSS?

Test Procedure in SPSS Statistics

1. Click Analyze > Regression > Linear…
2. Transfer the dependent variable, HDL, into the Dependent: box and then transfer the independent variable, physical_activity, and the dummy variable, normal, into the Independent(s): box using the appropriate buttons.
3. Click on the button.

Is interaction effect same as moderator?

You should consider the two terms to be synonymous. Although they are used in slightly different ways, and come from different traditions within statistics (‘interaction’ is associated more with ANOVA, and ‘moderator variable’ is more associated with regression), there is no real difference in the underlying meaning.

What is an interaction term in SPSS?

Interaction describes a particular type of non-linear relationship, where the “effect” of an independent variable on the dependent variable differs at different values of another independent variable in the model. This is called a two-way interaction.

What does an interaction term do?

Adding interaction terms to a regression model can greatly expand understanding of the relationships among the variables in the model and allows more hypotheses to be tested. Adding an interaction term to a model drastically changes the interpretation of all the coefficients.

What exactly is an interaction moderation effect?

1. What exactly is an interaction/moderation effect? When a third variable (X1) and an independent variable (X2) affect the dependent variable (Y) simultaneously. When a third variable (X1) reduces the effect of an independent variable (X2) on the dependent variable (Y)

How do you explain interaction terms in regression?

In regression, an interaction effect exists when the effect of an independent variable on a dependent variable changes, depending on the value(s) of one or more other independent variables.

How do you measure moderation effect?

The most common measure of effect size in tests of moderation is f2 (Aiken & West, 2001) which equals the unique variance explained by the interaction term divided by sum of the error and interaction variances. When X and M are dichotomies f2 equals the d2/4 where d is the d difference measure described above.

How is SPSS regression with moderation interaction example?

SPSS Moderation Regression – Example Data These 3 predictors are all present in muscle-percent-males-interaction.sav, part of which is shown below. We did the mean centering with a simple tool which is downloadable from SPSS Mean Centering and Interaction Tool.

When is an interaction effect statistically significant in SPSS?

*SPSS Two-Way ANOVA syntax as pasted from screenshots. /DESIGN=gender medicine gender*medicine. Following our flowchart, we should now find out if the interaction effect is statistically significant. A -somewhat arbitrary- convention is that an effect is statistically significant if “Sig.” < 0.05.

How to determine if a moderating effect exists?

We use the standard method of determining whether a moderating effect exists, which entails the addition of an (linear) interaction term in a multiple regression model. For this reason, you might often hear this type of analysis being referred to as a moderated multiple regression or as its abbreviation, MMR (e.g., Aguinis, 2004).

What are the R values for SPSS regression?

1 r = 0.10 indicates a small effect; 2 r = 0.30 indicates a medium effect; 3 r = 0.50 indicates a large effect.