A mediating variable, also known as a mediator, is a variable that explains the process through which two other variables are related. It is a third variable that comes between the independent variable and the dependent variable in a causal chain. The mediating variable is part of the causal pathway of an effect, and it tells you how or why an effect takes place.

Here are some key points to keep in mind about mediating variables:

• A mediating variable is caused by the independent variable and affects the dependent variable.
• It explains the relationship between the independent and dependent variables.
• Mediators are important to consider when studying complex correlational or causal relationships between variables.
• Mediation analysis tests whether a variable is a mediator using one of the two main methods – Analysis of Variance (ANOVA) or linear regression analysis.
• Mediation may either be partial or complete. In complete mediation, the mediator thoroughly explains the relationship between a dependent and an independent variable.
• Mediators tell you why and how an effect happens, while moderators help judge the external validity of your research.

Identifying mediating variables is important in research because it helps researchers understand the underlying mechanisms that explain the relationship between two variables. By including mediators in research, researchers can go beyond studying a simple relationship between two variables for a fuller picture of the real world.