Conceptual framework: Control variables

A control variable is a variable that is held constant to prevent it from influencing the outcome of a study.

When testing a cause-and-effect relationship, it is important to consider which variables might influence the relationship between your independent and dependent variables and control these so that your results are as accurate as possible.

Control variables in a conceptual framework

This is a continuation of an article explaining how to create a conceptual framework. Our example framework maps the relationship between “hours of study” (independent variable) and “exam score” (dependent variable).

To test whether there is a cause-and-effect relationship between “hours of study” and “exam score,” we also need to consider other variables that could potentially impact students’ exam scores.

For example, it is likely that if a student feels ill, they will get a lower score on the exam. Therefore, we’ll add “health” as a control variable.

Sample conceptual framework with a control variable

That means we should keep the variable “health” constant in our study – we’ll only include participants who are in good health on the day of the exam.

Moderating and mediating variables

There are often other variables that we might want to include in our conceptual framework: moderators and mediators.

These are variables that we think will influence a student’s exam score, but that we don’t necessarily want to hold constant. Instead, we measure moderators and mediators and include them in our analysis in order to better understand the cause-and-effect relationship.