Cronbach’s Alpha coefficients - How to interpret Cronbach’s Alpha

10. Januar 2020

Cronbach’s Alpha coefficients - How to interpret Cronbach’s Alpha

Cronbach’s Alpha: Simple Definition, Use and Interpretation

Cronbach’s alpha (or coefficient alpha), developed by Lee Cronbach in 1951, is a way to measure reliability, or internal consistency of a psychometric instrument. “Reliability” is how well a test consistently measures what it is supposed to measure. Low reliability would mean it’s measuring something else, or possibly nothing at all.

Reliability tests, like Cronbach’s alpha, are most commonly used to see if questionnaires with multiple Likert scale questions are reliable. These questions are designed to measure latent variables. A latent variable is a hidden or unobservable variable, like a person’s conscientiousness, neurosis or openness. These variables are notoriously difficult to actually measure; Cronbach’s alpha will tell you if the test you have designed is accurately measuring the latent variable you are interested in.

Cronbach's alpha simply provides you with an overall reliability coefficient for a set of variables (e.g., questions). If your questions reflect different underlying personal qualities (or other dimensions), for example, employee motivation and employee commitment, Cronbach's alpha will not be able to distinguish between these. In order to do this and then check their reliability (using Cronbach's alpha), you will first need to run a test such as a principal components analysis (PCA).