You have probably encountered the terms mediators and moderators at some point. However, only a few might know what these mean and how they are used in research.
We will not make things difficult by using technical terms and jargon. Instead, we will make it as simple as possible. Also, we will focus on the mediator vs moderator topic, along with a clear understanding of independent and dependent variables.
By the end of the blog, you will have a clear idea about the meaning of the mediator and moderator variables, the relationship between the two variables, and the differences.
Let’s dive right in!
What Is Mediation in Research?
Let’s say you are looking for a house to rent in the US. To get the right place to stay, you will either look for one online or hire a broker to find a house. In this scenario, the broker is the mediator. The mediator only partially explains the terms and conditions and other aspects. It is up to you and the landlord to finalize the deal.
Similarly, in research, the mediating variable provides a way for independent variables to influence a dependent variable. It also provides the ways and reasons the two variables are related to each other.
With reference to the example above:
➤ Independent variable – Customer (you)
➤ Dependent variable – Landlord
➤ Mediator – Broker or any online portal
In statistics, mediation analysis is used to run tests to understand whether a variable can be considered a mediator using linear regression analyses or ANOVAs.
There are two types of mediation: full mediation and partial mediation. Here’s what they mean:
➤ Full mediation refers to cases where the mediator gives a complete explanation of the ways the two variables are related to each other
➤ Partial mediation refers to the statistical relationship between the independent and dependent variables, even after taking the mediator out of the model
That will help you understand what a mediator is and how it plays a role in different aspects. Moving on, we will understand the meaning of a moderating variable before discussing the differences.
What Is a Moderator Variable?
Taking the same example of getting a rented place forward, let’s understand what a moderator is. Your broker has shortlisted a few houses and asked you to visit them. When you go through them, you find only a few that fit your budget. You go ahead and visit those with your broker.
In the above example, money plays the role of a moderator. Simply put, moderation strengthens or directs the relationship between two variables. In this case, money is a third variable that influences the relationship between the dependent and independent variables.
Moderation analysis refers to the degree to which the third variable influences the relationship between an independent and dependent variable.
Now that you have an idea of what a mediator and moderator are, let’s focus on the main point of this blog: mediator vs. moderator variables and how they are different.
Mediator vs Moderator Variables in Research
Understanding the difference between a mediator and a moderator is important to complete the research successfully. When you talk about mediators and moderators in your research, most of you confuse one with the other. To clear the air, here’s a detailed breakdown of the points showing how they are different from one another:
| Factors | Mediators | Moderators |
|---|---|---|
| Meaning | Explains the relationship between variables in the research platform | Affects the strength or direction of the relationship between two variables |
| Role | Acts as an intermediary or ‘go-between’ in the relationship between the variables | Changes the correlation between independent and dependent variables, but is not a part of the causal relationship between variables |
| Causal Pathway | Mediators are part of the causal pathway | Moderators are not part of causal pathways |
| Function | ‘How’ or ‘Why’ | ‘When’ or ‘Under what conditions’ |
| Visual | Draw an arrow from the independent variable to the mediator and then from the mediator to the dependent variable | Draw an arrow from the mediator to the relationship between the two variables |
Both moderators and mediators are equally important in any research. In the following section, we will discuss the mediation analysis and moderation analysis to further clear all your doubts. You can also learn about externship vs internship to familiarize yourself with these terms.
Mediation Analysis: Exploring the Process and Significance in Research
In research, you need two kinds of variables: dependent and independent variables. It is not possible to establish a relationship between the two without the mediator variable. Mediation analysis is used to understand whether a variable is a mediator or not. It is determined by using either of the two methods: Analysis of Variance (ANOVA) or linear regression analysis.
The mediator thoroughly explains the relationship between the independent and dependent variables. It is impossible to complete research if you take the mediator out of the model.
In the case of partial mediation, the mediator partially explains the relation because it is taken out of the model midway. There are cases where it is taken out midway, but it is one of the most important factors that affect the entire research.
You must follow a few guidelines to complete the mediation analysis:
➤ The independent variable should cause the mediator
➤ The mediator must influence the dependent variable
➤ The mediator must be the major factor in establishing a higher statistical correlation between the independent and dependent variables
Linear regression describes the connection between the variables by using a line to connect the data you observe. The process helps analyze how an independent variable affects the dependent variable. On the other hand, ANOVA is the process that analyzes how the means of three or more groups are different from each other.