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What does a non significant conditional effect at certain values of the moderator variable mean?
When testing the moderator effect of a variable, first, and the most important, is to test the interaction between the independent variable and the moderator variable. When this interaction is a non-significant effect we can statistically conclude that the moderator variable does not work as it.
Why is moderator not significant?
When there is no Significance interaction it means there is no moderation or that moderator does not play any interaction on the variables in question. However this doesn’t mean in practice there isn’t any interaction.
What’s the difference between moderation and interaction effect?
I’ve had conversations with seasoned researchers who were shocked to discover that moderation is simply an interaction effect. But again, interaction is a little more generic than moderation. Moderation distinguishes between the roles of the two variables involved in the interaction.
When is the moderator not significant, but the interaction?
An interaction implies that the effect of X on Y is not constant as A changes (and vice versa). If you decided to evaluate the effect of X or A at some other point on the number line then it might or might not be significant.
What is the effect of moderator on dependent variable?
We’re never interested in the effect of the moderator on the dependent variable. When we speak of interaction, we don’t usually distinguish between independent variable and the moderator. Either predictor could be considered to “moderate” the effect of the other. Mathematically, there is no distinction.
How to interpret moderation effects without a graph?
Moderation effects are difficult to interpret without a graph. It helps to see what is the effect of the independent value at different values of the moderator. If the independent variable is categorical, we measure its effect through mean differences, and those differences are easiest to see with plots of the means.