Item reliability indicates how consistently a set of instruments measures an overall response. Cronbach’s α (Cronbach 1951) is one measure of reliability. Two primary applications for Cronbach’s α are industrial instrument reliability and questionnaire analysis.
Cronbach’s α is based on the average correlation of items in a measurement scale. It is equivalent to computing the average of all split-half correlations in the data table. The Standardized α can be requested if the items have variances that vary widely.
Note: Cronbach’s α is not related to a significance level α. Also, item reliability is unrelated to survival time reliability analysis.
To look at the influence of an individual item, JMP excludes it from the computations and shows the effect of the Cronbach’s α value. If α increases when you exclude a variable (item), that variable is not highly correlated with the other variables. If the α decreases, you can conclude that the variable is correlated with the other items in the scale. Nunnally (1979) suggests a Cronbach’s α of 0.7 as a rule-of-thumb acceptable level of agreement.