What is moderator analysis?

A moderator analysis is used to determine whether the relationship between two variables depends on (is moderated by) the value of a third variable. 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.

How do you test for moderated mediation?

In order to test for moderated mediation, some recommend examining a series of models, sometimes called a piecemeal approach, and looking at the overall pattern of results. This approach is similar to the Baron and Kenny method for testing mediation by analyzing a series of three regressions.

What is the difference between moderator and mediator?

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship. In contrast, a mediator is the mechanism of a relationship between two variables: it explains the process by which they are related.

How do you analyze the moderation effect?

A moderation analysis typically consists of the following steps.

1. Compute the interaction term XZ=X*Z.
2. Fit a multiple regression model with X, Z, and XZ as predictors.
3. Test whether the regression coefficient for XZ is significant or not.
4. Interpret the moderation effect.
5. Display the moderation effect graphically.

Can a moderator be a mediator?

Mediation and Moderation. Indeed, mediators and moderators can and should be considered in both experimental and nonexperimental designs, thus the appropriateness of the interchangeable terms.

What is moderating effect in research?

the effect that occurs when a third variable changes the nature of the relationship between a predictor and an outcome, particularly in analyses such as multiple regression. If the prediction is different across the two groups, then teaching style is said to have produced a moderating effect. …

Why do we use moderators?

Moderating variables Moderators usually help you judge the external validity of your study by identifying the limitations of when the relationship between variables holds. For example, while social media use can predict levels of loneliness, this relationship may be stronger for adolescents than for older adults.

What is a moderator variable in Stata?

| Stata FAQ. A moderator variable is a variable involved in an interaction with another variable in the model such that the effect of the other variable depends upon the value of the moderator variable, i.e., the effect of the other variable changes depending on the value of the moderator.

How do you do mediation analysis in Stata?

SEM in Stata Thesemcommand allows conducting mediation analysis as long as boththe dependent variable and the mediator variable are continuous variables(and all assumptions are met) The basic command is built on tting the two regression models presentedbefore sem (M <- X C1 C2)(Y <- M X C1 C2)

How to compute the conditional indirect effects in Stata?

In order to compute the conditional indirect effects we need to have access to regression coefficients from two different models; one model with the mediator as the response variables and another model with the dependent variable as the response variable. The easiest way to do this in Stata is to use the sem command introduced in Stata 12.

How to compute the conditional indirect effects of a moderator variable?

So, the interaction terms need to go in the models for both m and y. Thus the sureg command looks like this: Next, we use the nlcom command to compute the conditional indirect effects for each of the levels of the moderator variable. For level one multiply each of the interaction terms, wx2 and wx3 by zero.