I used to think that I knew that. However, my last results made me quite confused. Basically, the variable that a propose a moderation effect has a direct negative effect in my dependent variable. Although, when the variable is added as a moderator, the effect is positive. How can I interpret that? They both had significant coeficients.
moderation occurs when the relationship between two variables depends on a third variable. The third variable is referred to as the moderator variable or simply the moderator. The effect of a moderating variable is characterized statistically as an interaction;[1] 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. Specifically within a correlational analysis framework, a moderator is a third variable that affects the zero-order correlation between two other variables, or the value of the slope of the dependent variable on the independent variable. In analysis of variance (ANOVA) terms, a basic moderator effect can be represented as an interaction between a focal independent variable and a factor that specifies the appropriate conditions for its operation
Do your effects involve a pair of dummy variables, or is the original independent variable you are examining continuous? Alternatively, your moderation effect might involve two continuous variables.
How you can say that if a variable is added as a moderator it's effect must be positive? Can you please provide some supportive reference for this.
Moreover, according to me it's sign simply tell the type of combine impact they ( moderator and independent variable) have on dependent variable
For example: if corruption(moderator) rises external/ internal resources ( independent variable) don't utilize in a way they should be
then it can be justified to have a negative impact of its interaction term on economic growth. As it is based on the theory.
In the case of the moderator, it combines with an independent variable to derive interacting variable, which is regressed on dependent variable. in the results, we will get coefficient for this, which will be interpreted withing statistical restrictions. whether a variable may be used as moderator or predictor, decision is made from theoretical basis.
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