# Likert-Scale

Why do we need a Likert scale? Let's assume you have formulated a hypothesis in which a variable that cannot be measured directly, a so-called latent variable, occurs. So how do you measure this variable in your questionnaire?

Latent variables are, for example, physical well-being or environmental awareness. Why are these variables not directly measurable? Of course, you could simply ask in your questionnaire, "What is your level of environmental awareness?"

However, you will find it very difficult or very inaccurate to measure environmental awareness with just this one question, because environmental awareness consists of several dimensions.

The first person thinks to himself, I am in an animal welfare organization and take care of animals in need, and ticks "very high", but on the other hand makes a long-distance trip by plane three times a year.

The next person thinks, well, my awareness of the environment is very high, I know that you should actually separate the garbage and not drive the car all the time, so my awareness of the environment is high, but I don't comply. Does that person then tick "high" or "low"?

You can, of course, just ask this single question to measure environmental awareness, but you won't be able to do much with the answers.

## Scales

In order to be able to adequately measure latent variables such as environmental awareness, scales are now used. A scale is a group of questions, e.g., question 1, 2, 3, and 4, with response categories ranging from, e.g., "strongly agree" to "strongly disagree." Together, these questions serve to measure a latent variable.

By using multiple questions, your measurement becomes more accurate. Such a scale is also called a multi-item scale.

The best known scale is the Likert scale. This is a method used to measure personal attitudes. The Likert scale consists of several questions, so-called items. Items are statements that record the respondent's level of agreement or disagreement. Thus, respondents can indicate how much they disagree or agree with a statement on a multilevel response scale.

Usually, a 4- or 5-level rating is used.

4-level rating:

• applies (1)
• rather applies (2)
• rather not applies (3)
• does not apply (4)

5-level rating:

• applies (1)
• rather applies (2)
• partly-partly (3)
• rather not applies (4)
• does not apply (5)

Whether a middle category is useful or not cannot be answered in a blanket way.

In some cases, it makes sense for respondents to have a "neutral" middle category available to avoid being pushed in one direction. On the other hand, there is a risk that many respondents will like to choose the middle category, which could make your results less meaningful.

## Question with a Likert scale

Now the next question is, how do I come up with the right questions? Do I just make up the questions myself?

This is not a good idea, because in that case you would have to go to great lengths to check whether your questions really measure the latent variables correctly.

The clean way is to do a literature and scale search and find out if there are already validated questions that you can use to measure your variables.

What is the easiest way to start a literature and scale search? We just start "quick and dirty" and "google" for "environmental awareness questionnaire".

## Likert scale and indexing

So, now you send out your questionnaire and have it filled out. Let's assume that you have received enough responses and are finished with the survey. What do you do with the answers? Let's take a look at that now.

So that we don't have too much text, let's just use this example again:

The participants of your survey have ticked something from "agree" to "disagree" for questions 1 to 4. Now you can export the finished survey to Excel or DATAtab, then each row shows a respondent and the columns show the 4 questions. The first person has ticked "2" for question 1, "1" for question 2, "3" for question 3 and "2" for question 4.

Now you want to measure your latent variable with these four questions. Likert scales are often assumed to have a metric scale level in practice. Strictly speaking, the answers on a Likert scale are ordinally scaled, because the distances between the answers are probably not perceived as equal by the survey participants.

Therefore, the most common way is that you build a so-called mean index. To do this, you simply calculate the mean of each row. You now have an estimate for your latent variable.

You can also easily create the mean value index with DATAtab. To do this, copy your data into this table and click on "Transform data". Now click on "Index formation" and select questions 1 to 4. Then click on "Mean value index" and enter the name for the new variable - done! Now you can check if your questions really measure a latent variable. You can do this with the so-called Cronbach's alpha.

Cite DATAtab: DATAtab Team (2023). DATAtab: Online Statistics Calculator. DATAtab e.U. Graz, Austria. URL https://datatab.net