Statistics – Cronbach’s alpha

Hi, after my webinar in beginning of July about factor analysis and creating index variables of variables that is correlated to each other, I think it’s worth telling you about a validation method before creating index variables. Index variable could be a sum/mean of some questions (variables) that is correlated to each other, ex satisfaction index.

The method to check correlations between a couple of variables at the same time, is called Cronbach’s Alpha. The alpha value you will get is between 0 and 1  and is like a “average correlations measure” for a couple of variables – often questions from a questionnaire. It should be above 0.7 – a common treasure value.

A rule is: Just use variables with positive correlations. Also be aware of that the alpha-value will be higher if you have more variables, so if you have more than 5 variables and one of them has a bad correlation to the other – the alpha value could be higher anyway.

Demo:

Command in SPSS Statistics: Analyze – Scale – Reliability Analysis

From the factor analysis I found out that these 3 variables within the red oval, belongs to each other (correlated to each other):

So as they all is positive correlated I want to measure the Cronbach’s alpha, to see how strong all 3 correlates to each other at the same time, so I put these 3 variables (questions) into the right box at “items” in the command (reliability analysis):

Result:

I’m not so happy, as the alpha value (0,62) is not above 0,70. What happen if I add the 4th variable that is positively correlated to these 3, if you look at the factor analysis matrix above (“it’s important to keep the flow in the traffic…”).

Result:

So it’s closer to 0,7, but I cannot be sure that this is because of a good correlation among all 4, as I also know that the alpha value gets higher when you add an extra variable.

So the reason why the alpha value is not so good as I hoped for, is because of the correlations among these variables is not very high. I will talk more about correlations next week.

Here is an example of 3 other variables that has much higher correlations, and what happens to the Cronbachs alpha:

Result:

I got a good result, and could now create an index between these 3 variables.

Help: If you double click the result table and then right click on Cronbach’s Alpha you will get a yellow box with information:

Let’s show you the correlations of these variables next week!

/Gunilla Rudander

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