Chronbach’s Alpha is a way to measure the internal consistency of a questionnaire or survey.
Cronbach’s Alpha ranges between 0 and 1, with higher values indicating that the survey or questionnaire is more reliable.
The following example shows how to calculate Cronbach’s Alpha for a dataset in SAS.
Example: How to Calculate Cronbach’s Alpha in SAS
Suppose a restaurant manager wants to measure overall satisfaction among customers, so she sends out a survey to 10 customers who can rate the restaurant on a scale of 1 to 3 for various categories.
We can use the following code to create the dataset that holds the survey responses in SAS:
/*create dataset*/
data survey_data;
input Question1 Question2 Question3;
datalines;
1 1 1
2 1 1
2 1 2
3 2 1
2 3 2
2 3 3
3 2 3
3 3 3
2 3 2
3 3 3
;
run;
/*view dataset*/
proc print data=survey_data;
We can use the proc corr function to calculate Cronbach’s Alpha:
/*calculate Cronbach's Alpha*/
proc corr data=survey_data alpha;
var Question1-Question3;
run;
The output tables provide us with a lot of information, but the main value we’re interested in is the Raw value in the table titled Cronbach Coefficient Alpha.
From this table we can see that Cronbach’s Alpha turns out to be 0.773.
The following table describes how different values of Cronbach’s Alpha are usually interpreted:
| Cronbach’s Alpha | Internal consistency |
|---|---|
| 0.9 ≤ α | Excellent |
| 0.8 ≤ α | Good |
| 0.7 ≤ α | Acceptable |
| 0.6 ≤ α | Questionable |
| 0.5 ≤ α | Poor |
| α | Unacceptable |
Since we calculated Cronbach’s Alpha to be 0.773, we would say that the internal consistency of this survey is “Acceptable.”
Bonus: Feel free to use this Cronbach’s Alpha Calculator to find Cronbach’s Alpha for a given dataset.