Mediator Variables – Conceptual Framework

Published 16 October, 2023

A mediator is an inner part of the relationship between cause and effect. Students pursuing a Masters’s or undergraduate often have confusion between moderator and mediator variable. In this article, our professional by using example is providing the proper explanation about the mediator variable.

What is the mediator variable in the conceptual framework?

The mediator variable is the variable that explains the correlation between the two variables.  It is a variable in a conceptual framework which helps the researcher in developing the understanding about the way independent variable influence the dependent variable.

The mediator variable helps in identifying the facts that govern the relationship between the dependent and independent variables.

Expanding mediator variable in Conceptual Framework: Example

A researcher is performing research for identifying the influence of using a laptop at night on sleeping hours. In this example, the use of a laptop is the independent variable and sleeping hours are the dependent variable. Now for expanding the conceptual framework let us add a mediator variable that is mental health.

You need to include the mediator variable between dependent and independent variables in cause-effect relationships.

If you still have any confusion related to independent and dependent variables then you can read article Conceptual frameworks.

Students found interpreting the mediator variables as a very much difficult task. You need to be more careful at the time of concluding. Mediator variables must be often underpinned by statistical analysis.

How conceptual framework looks when mediator variables are involved?

Let’s, look at the example for analyzing and developing the understanding of the way conceptual framework looks when we add a mediator variable in it.  Example: Researchers perform research for identifying influencing the use of laptops at night on the number of sleeping hours.

In this illustration the relationship between the dependent and independent variables plays a central role. Here, the cause-effect relationship is that less time a person uses a laptop he or she will be able to sleep more hours at night.

Now let us add a mediator variable that is mental health.  The more hours a person spend working on a laptop at night, this will create mental pressure as a result an individual will not able to sleep properly at night.

By adding the moderator variables in the conceptual framework we have strengthened the relationship between cause and effect.  We have also been able to explore two main variables of the study.

You should not get confused between mediator and moderator variables in the conceptual framework. Illustrating the difference, you should think about “mental health” a moderator which we have included in our conceptual framework in the article on Moderator variables.

Here, Moderator Mental health is not a mediator variable, as the number of hours a person uses a laptop does not influence mental health.


From the above article, it has been concluded that mediator variables explain the relationship between dependent and independent variables. Another fact which has been discovered is that the mediator variable comes in between dependent and independent variables.

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