Using scales to measure constructs is widespread in the social sciences and beyond.  To support the application of these scales, researchers and practitioners need to show evidence of appropriate reliability and validity.  Many different types of reliability exist, but internal consistency reliability is perhaps the most popular.  Even yet, many metrics exist to provide evidence of internal consistency reliability, but Cronbach’s alpha is perhaps the most popular of these.  For this reason, I provide a guide below of how to calculate Cronbach’s alpha in Jamovi.  If you have any questions or comments after reading, please contact me at MHoward@SouthAlabama.edu.

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Typically, I begin my guides with a brief review of the statistic; however, one of my prior DBA students, Chad Marshall, wrote a fantastic introduction to Cronbach’s alpha which was previously featured on MattCHoward.com.  If you need to learn more about Cronbach’s alpha, click here to read it.

Once you are familiar with Cronbach’s alpha, we can then use Jamovi to calculate it.  If you don’t have a dataset, you can download the example dataset here. In the dataset, we are investigating the relationship of job satisfaction and job performance, but we need to see whether our job satisfaction measure is internally consistent first.

Also, this file is in .xls format, but Jamovi cannot open this format.  To learn how to change this .xls file to a .csv file, which Jamovi can open, please click here.  Also, the pictures below are a little small on the page. Click on the link above each picture to view a larger version of the picture in a new window.

The data should look something like this:

Cronbach’s Alpha in Jamovi Picture 1

If your dataset looks differently, you should try to reformat it to resemble the picture above. The instructions below may be a little confusing if your data looks a little different.

Once you have the data open, the first step is to click on the Factor button at the top.

Cronbach’s Alpha in Jamovi Picture 2

And then click on Reliability Analysis.

Cronbach’s Alpha in Jamovi Picture 3

Now, you should get a screen like this:

Cronbach’s Alpha in Jamovi Picture 4

This step is the most confusing, however.  In this window, Jamovi orders the variables by their type: continuous, ordinal, nominal, and categorical.  For our scales, however, it interpreted our first two variables as nominal and all the others as continuous.  This resulted in the items for our scales being out of order.  So, we have to be careful with the items we include in our reliability analysis.

Let’s start with job satisfaction.  Scroll down and find the first job satisfaction item.  Click on it, and then click the arrow pointing right next to the items box.

Cronbach’s Alpha in Jamovi Picture 5

Now, scroll back up and add the other job satisfaction items.  Don’t include the overall scale average!

Cronbach’s Alpha in Jamovi Picture 6

And Jamovi now automatically calculates our Cronbach’s alpha.  Nice!

Cronbach’s Alpha in Jamovi Picture 7

From this, we can see that the Cronbach’s alpha of our job satisfaction scale is .86.  As we know from reading our guide on Cronbach’s alpha, this result suggests that our scale demonstrates appropriate levels of internal consistency.  You can also go back and try to calculate the Cronbach’s alpha for job performance.  It should be .75.

Hopefully from this practice, you should now be able to calculate a Cronbach’s alpha on your own.  Good work!  As always, if you have any questions or comments, please email me at MHoward@SouthAlabama.edu.

As an aside, Jamovi can also calculate McDonald’s omega using the same window seen above.  I recently had a reviewer criticize my manuscript for not including McDonald’s omega, and I had never calculated it before.  So, I did a Google search and discovered that Jamovi is one of the few programs that can calculate McDonald’s omega.  Fortunately, I had just downloaded Jamovi at the recommendation of a friend, so I was able to include this statistic and have my manuscript accepted for publication.  Thanks Jamovi!