MBA Group firstname.lastname@example.org introduced articles on reliability analysis in SPSS. This article focuses on the introduction of theory and practice analyzing Cronbach's alpha reliability.
What is Cronbach’s alpha?
-Cronbach’s coefficient alpha provides an indication of the average correlation among all of the items that make up the scale. Values range from 0 to 1, with higher values indicating greater reliability. While different levels of reliability are required, depending on the nature and purpose of the scale, Nunnally (1978) recommends a minimum level of 0.7. Cronbach's alpha measure of internal consistency, how closely related a set of items are in a group.
-Cronbach alpha values are dependent on the number of items in the scale. When there are a small number of items in the scale (fewer than ten), Cronbach alpha values can be quite small. In this situation it may be better to calculate and report the mean inter-item correlation for the items. Optimal mean inter-item correlation values range from .2 to .4 (as recommended by Briggs & Cheek, 1986). Cronbach's alpha is not a statistical test , but it is a coefficient of consistency.
The criteria used to evaluate the reliability scale:
– Remove the observed variables if “Corrected Item-Total Correlation” less than 0.3.
– The observed variables have “Corrected Item-Total Correlation” small (less than 0.3) will be removed and the scale is accepted as Alpha reliability coefficient greater than 0.7 .
Practice analyze Cronbach's alpha in SPSS
-Open SPSS data file.
-Select Analyze menu> Scale-> Reliability Analysis
Select the items in the same factor through the right column,
Then click on Statistic, check the box “Scale if the item deleted”. Then click Continue, then click OK
Cronbach’s alpha results will show as follows:
Conclusion: Cronbach's alpha of the scale was 0.869, the “Corrected Item-Total Correlation” in the scale are greater than 0.3 and no cases eliminate observed variables that can make the Cronbach's alpha of the scale this is greater than 0.869( last column). So, all the observed variables are accepted and will be used in subsequent factor analysis.
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