to study the impact of a modertor variable on the relationship between the independent and the dependent variable, is the presence of a significant relationship between the independent and the dependent variable necessary? I mean what if in the model, the effect of the independent variable on the dependent variable is insignificant, but the effect of the interaction between the independent and the moderator is significant? does it imply that something is wrong? if not, then how to interpret this result?
@SolomonGetachew Жыл бұрын
When the effect of the independent variable on the dependent variable is insignificant, but the effect of the interaction between the independent variable and a moderator is significant, it suggests that the relationship between the independent variable and the dependent variable is conditional upon the level of the moderator variable. Example: Main Effect (No Interaction): You find that there is no significant relationship between sleep duration and academic performance on its own, suggesting that just the amount of sleep alone doesn't predict academic performance. Interaction Effect: However, when you introduce caffeine consumption as a moderator, you find a significant interaction effect. This implies that the impact of sleep duration on academic performance varies based on caffeine consumption. For students who consume little to no caffeine: You might find that longer sleep duration is associated with better academic performance, suggesting that for these students, sleep matters. For students who consume a lot of caffeine: Here, sleep duration might not have a significant impact on academic performance. These students seem to perform relatively consistently, regardless of their sleep duration, as long as caffeine is in the equation. I hope you got it clear.