Knowing the difference between conceptual variables and actual measures is key for anyone in the social sciences, whether Business, Psychology, or anything else. Being able to take abstract ideas and turn them into concrete measures is essential for research and practice. For this reason, I usually have a unit on this topic near the beginning of any stats course. Even higher-level stats students can usually use a refresher on conceptual variables and actual measures, as the differences may be difficult to grasp. To help in this endeavor, I created this brief guide on conceptual variables and actual measures.
It is important to first understand independent and dependent variables. If you remember, the difference between independent variables and dependent variables is their relationship with each other. Independent variables have an effect on dependent variables (Independent -> Dependent). If you need a refresher on the two concepts, here is a link: https://mattchoward.com/independent-variables-and-dependent-variables/ .
On the other hand, the difference between conceptual variables and actual measures does not involve the relationship between variables. Instead, a conceptual variable is any construct/idea/concept/variable that we can conceptualize but not completely measure. For example, researchers are often interested in the concept of depression, which is a conceptual variable. There is no method to 100% gauge someone’s depression. People do not have a depression number floating above their head. So, we must use an actual measure to represent depression, such as a self-report survey with items akin to, “I am sad all the time.” So, in this example, depression is the conceptual variable, and the self-report survey is the actual measure.
Make sense? The following might help even more. Let’s try to figure out whether some examples are conceptual variables or actual measures. Below are some descriptions of things. Try to figure whether each are conceptual variables or actual measures before reading the answer.
A1: Conceptual Variable
Q2: How much someone talks during a 10 minute meeting.
A2: Actual Measure
Q3: The number of pounds someone can lift.
A3: Actual Measure
A4: Conceptual Variable
Q5: Workplace performance
A5: Conceptual Variable
Q6: Supervisor ratings of performance
A6: Actual Measure
Did you get those correct? If so, great! If not, try to review the topic again. Then, try to answer the questions again. Remember, if the thing is not something that you can absolutely measure and record, then it is probably a conceptual variable.
Now, let’s think about conceptual variables and actual measures along with independent variables and dependent variable. A conceptual variable can be an independent variable or a dependent variable, and an actual measure can also be an independent variable or a dependent variable. Whether something is an independent variable or dependent variable has no impact on whether it is a conceptual variable or actual measure. For example, we can believe that depression reduces life satisfaction. In this example, depression is an independent conceptual variable, and life satisfaction is a dependent conceptual variable. We can also believe that self-report survey of depression will have a negative relationship with a self-report survey of life satisfaction. In this example, the self-report survey of depression is an independent actual measure, and the self-report survey of life satisfaction is a dependent actual measure. Usually, we do not make claims about the relationship between an independent conceptual variable and a dependent actual measure, and vice versa, but I guess it could happen.
Now, to finish, let’s look at the picture below.
This picture represents a simple research relationship. In research, we will make a theory or hypothesis about a relationship between two (or more) conceptual variables. This is represented in the bottom dotted-square. Then, we create actual measures that are meant to represent the conceptual variables. The relationship of these actual measures with the conceptual variables is represented with the dotted-arrows pointing down. We can perform measure development and validation studies to support the validity of our measures, but their relationships with conceptual variables is always inferred. Next, we perform a research study to determine the relationship of our actual measures, which is represented in the top dotted-box. When we do this, we can obtain an observed relationship between the actual measures, which is represented by the solid arrow in pointing right. Because we assume that our actual measures are representative of our conceptual variables, we can also infer that the observed relationship between the actual measures is similar to the relationship between the conceptual variables. Together, this is the underlying idea behind most research in the social sciences. Make sense?
Let’s use a final example to help clarify things even more. Let’s say we have the following hypothesis: Extroversion is positively related to happiness. To study our conceptual variables (extroversion and happiness), we need to create actual measures. We can use a scale to measure extroversion that includes items similar to “I talk a lot,” and respondents can answer on a 1 (Strongly Disagree) to 7 (Strongly Agree) scale. We can also use a scale to measure happiness that includes items similar to “I feel joyful,” and respondents can answer on a 1 (Strongly Disagree) to 7 (Strongly Agree) scale. Once the scales are created and participants have provided responses, we can correlate the two measures. Let’s say the correlation between the two actual measures is very small and non-significant. We would then assume that the relationship between the two conceptual variables is also very small and non-significant. Thus, we have used actual measures to draw inferences about conceptual variables.
Does that clarify things? Let me know if you are still confused about the difference between conceptual variables and actual measures. My email address is email@example.com. I can try to provide more info and examples. Otherwise, good job understanding the difference between conceptual variables and actual measures!