Mediating variable is a variable that explains the correlation between the two variables

What is a mediator?
A mediator is an inner part of the relationship between cause and effect. A lot of novices researchers have confusion between moderator and mediator variables. Let us first understand what we mean by the mediator variable and its application in the conceptual framework.

What is Mediating Variable?
Mediating variable is a variable that explains the correlation between the two variables. It finds its use in the conceptual framework and helps the researcher to develop a thorough understanding of the way in which the independent variable influences the dependent variable. It primarily aids in helping to understand the facts given the relationship existing between the independent and dependent variable and the way in which the independent variable influences the dependent variable. In order to understand clearly, we can name the mediating variable as an intervening variable, which comes in between the independent and dependent variables and tells that how these variables are interrelated. For example, if variable X causes the variable Y, then the mediating variable A will identify the factor which shows the kind of relationship X and Y have with each other.

The application of mediator variable in the conceptual framework
Let us look at an example to understand the application of the mediator variable in the conceptual framework. If a researcher is studying the impact of late-night phone usage on the sleeping hours of the respondents, the independent variable is going to be the phone usage and the number of hours spent sleeping be the dependent variable. Now, for the purpose of expansion of the conceptual framework, the mediating variable is going to be stress level. The mediating variable is introduced between the dependent and independent variable in the process of establishing cause-and-effect relationships between the dependent and the independent variable.
A lot of researchers find it challenging to interpret the mediating variable. At the time of analysis and interpretation of the results, the mediating variable has to be underpinned by statistical analysis.

The look of the conceptual framework when the mediating variable is pitched in

Let us understand with an example, how the conceptual framework appears when a mediator variable is added to it. For instance, researchers undertake research on the impact of using smartphones at night and the number of sleeping hours. In this illustration, the relationship between the dependent and independent variables plays a vital role. Here, the cause-effect relationship is that the less time a person spends on the smartphone at night, the more he or she will be able to sleep in terms of hours at night. By pitching in moderator variables in the conceptual framework the researcher is able to strengthen the relationship between the cause and effect.
As a researcher, at this stage, it is a possibility to get confused between mediator and moderator variables in the conceptual framework. Illustrating the difference, you should think about the “stress” a moderator
Here, Moderator “Stress level” is not a mediator variable, as the number of hours a person uses a laptop does not influence stress levels but the lack of sufficient sleep does.
Hence, the moderator and mediator are both two independent variables that are specified by the researcher for depicting the relationship between the variables The moderating variables affect the other variables by showing their impacts on the other variables. While mediating variables show the relationship between the variables by elucidation the causal relationship.

What is Moderating Variable?

The job of a moderator is the influence it has on the level, direction, and presence of the relationship that exists between the variables. It explicitly states the researchers understanding that for whom, when, or under which circumstances the relationship will hold true. Moderating variables find their usage in judging the external validity and bring to the surface the limitation of “when” the relationship holds between the variables. For instance, social media usage can predict well the levels of loneliness amongst the users but this relationship between the usage pattern and loneliness is going to differ according to the age of the respondents. This means that age is a moderator in this case.
The nature of moderators can be:

• Categorical variables: these could be the ones that cannot be quantified and are categorical in nature. Such as ethnicity, race, religion, health status, etc.
• Quantitative variables: these are the ones that can be quantified in numbers such as age, weight, height, income, etc.

In the above flowchart example, without the moderator gender, the statistical significance of the fundamental relationship between work experience and salary can be established. To further study the impact of gender on the above relationship, where gender is the moderating variable, multiple regression analysis is carried out where gender identity is added to the basic model.

The difference between Mediating Variable and Moderating Variable:

On one side, the mediating variable explains the process through which the relationship between the independent variable can be explained. The moderating variable which is also called the moderator affects the strength and direction of that relationship. The inclusion of both these variables in the research helps to go beyond studying a basic relationship and gives a more holistic picture of the real world. This mediating and moderating variables help significantly when studying complex and causal relationships between the variables. The mediating variable is primarily a go between two variables. The flow chart description of the inclusion of mediating variable states that an arrow is drawn from the independent variable to the mediating variable and then further on from the mediating variable to the dependent variable. In the case depicting a moderating relationship, one can draw the arrow from the moderator to the relationship between the independent and dependent variables.
The inclusion of both these variables helps in overcoming the different research biases such as the observer bias, survivorship bias, under coverage bias, etc.

Example of the application of mediator Variable:

What exactly is a mediator, we know? The Mediator definition talks about the intervening factor or mediating variable between the independent and dependent variable, elucidating their causal relationship. So, let us look at the mediating variable example to comprehend the idea unmistakably
Mind maps; assist the learners in mugging and recalling the content more effectively and easily, as they invigorate and enrich their imagination, they tend to strengthen the process of learning effectively. With the inclusion of the mediating variable, a model can be created that can help in further understanding and elaborating the relationship between the independent and the dependent variable. Mind maps will be the independent variable and it has an effect in predicting and measuring the dependent variable which is an effective recalling and memorizing process. The mediating variable here is invigorated and enhanced imagination. TO explain more explicitly, one can say that, the mediator ‘invigorated and enhanced imagination’ and the independent variable ‘Mind maps’, are predicting the influences on the dependent variable ‘Recalling and Memorizing’.
Example of the application of Moderator Variable:

The moderation definition explains that the moderator is the variable that gives direction or exerts influence on the overall relationship between the two variables. It can work both ways. It can either make the relationship between the variables strong or even reduce the extent of the relationship between the variables.
The existence of a moderator is only justified and well-defined when there are two variables that have a relationship with each other in which any kind of change brought in one variable can impact the position of the other variable. The moderating variable is a third factor or party and it also has a very strong influence on what direction and shape would the relationship between the two variables take forward.

The moderating variable can be quantitative or qualitative in aspect. If the moderating variable is in quantifiable terms or numeric and the change in its numbers impacts the overall relationship between the dependent and independent variable then it is termed a quantitative moderating variable. Age, subjects, grade, and income are some examples of this. On the contrary, the qualitative moderating variable considers the qualitative properties of the variable. These could such as gender, racial differences, religious differences, the difference in the level of education, etc.

Let us look at the examples of the moderating variable to understand its application

In certain research, the researcher can put across a statement that knowing many languages can enhance the learner’s memory capacity but the age in which the language has been acquired plays a vital role in it. If the learner is young, the memory capacity is more as compared to older age.
In this above case, age is a quantitative moderating variable and the quantity or numeric representation gives direction to the relationship of learning many languages with memory capacity improvement. As the age of the learner increases, the memory capacity will be less effective.

To further understand the application of qualitative moderating variables, let us look at this example:

The researcher wants to understand how job satisfaction has an impact on the performance of employees. However, the criterion for job satisfaction will not be the same for both genders.
Gender, here becomes the qualitative moderating variable and it will define the level of satisfaction that an employee receives from his job and ultimately its impact on his performance.
Women tend to achieve the level of satisfaction more easily as compared to men so it will have a different kind of impact on women when it comes to performance on the job as well.

Advantages of using the Mediator and Moderator Variable in the Conceptual Framework of your research:

These two variables in their own way, play a very significant role for the researcher as they aid in specifying the research in terms of emphasizing the relationship and the influences of the third-party factors. It adds to strengthen the relationship between the dependent and the independent variable and gives more clarity to the causal effects of the relationship
Likewise, the researcher uses the moderating variable to exhibit the conditions or to explicitly specify the factors which would in some way influence the outcomes of the research. They add strength to the research, and the purpose is not as basic as studying the variables and the relationships that come with them but rather broadening the horizons of the research and incorporating the many aspects within the research which are different from the ones that have already been established.

Frequently Asked Questions:
a) What other name can we call a mediator variable:
There can be many names for the mediator variable. This is so because it qualifies to be a variable that works or behaves as a variable that intervenes between the dependent and the independent variable and highlights the depth of the relationship that exists between them. Hence, another word for the mediator variable would be “intermediary” or “negotiator”.

b) What is the meaning of moderator?
The moderator is an identity that modifies or brings in a change in something. In the context of research, moderator means a variable or third factor, which affects the other variables and establishes changes in their relationship. Moderator variables can change the relationship by simply changing their own nature and characteristics, or you may call them properties.

c) What are the significant points of difference between the moderator and a mediator?
One of them shows the link and the other changes or influences the relationship and link. Further on, the mediator variable supports the independent variable to exhibit the relationship it has with the dependent variable and the moderator is the influencer that directs the relationship and the link that is there in the variables with each other.

d) Does Mediation hold any different meaning in psychology?
In the field of psychology, mediation means getting the support of a third person or an intervening party that would assist the preexisting parties to resolve the dispute or conflict that exists. In psychology, it can also mean the response that can be generated by a stimulus.

e) What do we understand by Mediating effect?
Mediating effect means the situation or process in which the third party or factor shows the link or connection that is there between the two variables.