The Cronbach"s Alpha....

Cronbach's Alphas

What does Cronbach's alpha mean? 

Cronbach's alpha is a measure of internal consistency, that is, how closely related a set of items are as a group.    It is considered to be a measure of scale reliability. 

Cronbach's alpha is the most common measure of internal consistency ("reliability"). It is most commonly used when you have multiple Likert questions in a survey/questionnaire that form a scale and you wish to determine if the scale is reliable. If you are concerned with inter-rater reliability, we also have a guide on using Cohen's (κ) kappa that you might find useful.

A researcher has devised a nine-question questionnaire to measure how safe people feel at work at an industrial complex. Each question was a 5-point Likert item from "strongly disagree" to "strongly agree". In order to understand whether the questions in this questionnaire all reliably measure the same latent variable (feeling of safety) (so a Likert scale could be constructed), a Cronbach's alpha was run on a sample size of 50 workers.

SPSS Output for Cronbach's Alpha

SPSS produces many different tables. The first important table is the Reliability Statistics table that provides the actual value for Cronbach's alpha, as shown below:

Published with written permission from SPSS, IBM Corporation.

From our example, we can see that Cronbach's alpha is 0.805, which indicates a high level of internal consistency for our scale with this specific sample.

Item-Total Statistics

The Item-Total Statistics table presents the "Cronbach's Alpha if Item Deleted" in the final column, as shown below:

Published with written permission from SPSS, IBM Corporation.

This column presents the value that Cronbach's alpha would be if that particular item was deleted from the scale. We can see that removal of any question, except question 8, would result in a lower Cronbach's alpha. Therefore, we would not want to remove these questions. Removal of question 8 would lead to a small improvement in Cronbach's alpha, and we can also see that the "Corrected Item-Total Correlation" value was low (0.128) for this item. This might lead us to consider whether we should remove this item.

In the paper, this is the right way to explain about the cronbach alpha

We used the Cronbach’s alpha coefficient to assess the inter item consistency of our
measurement items. Table 5 summarizes the loadings and alpha values. As seen
from Table 5, all alpha values are above 0.6 as suggested by Nunnally and Berstein
(1994).