I have a questionnaire for a study to see the satisfaction pattern of patients visiting the OPD of a hospital? I am asked to see the Cronbach's alfa? I am searching but also waiting some easy explanation from you also! So please.....
you select from the SPSS tools: Analyze, ..Scale,...Reliability analysis,,,
then you select all the scale items, {the default setting is to give Cronbach's alpa}, you then hit OK
Dear Rajat, the input data should have the measure ordinal or scale. Cronbach's alpha may not be the best way to establish reliability. A principal component analysis might be more appropriate.
PCA and Cronbachs' alpha, both can be used for the better reliability measurement.
Dear Rajat Sanker Roy Biswas,
read this simple answer from Knowledge Base web-site I hope you find it beneficial. Thanks
In SPSS, how do I compute Cronbach's alpha statistic to test reliability?
Suppose you wish to give a survey that measures job motivation by asking five questions. In analyzing the data, you want to ensure that these questions (q1 through q5) all reliably measure the same latent variable (i.e., job motivation). To test the internal consistency, you can run the Cronbach's alpha test using the reliability command in SPSS, as follows:
RELIABILITY /VARIABLES=q1 q2 q3 q4 q5.
You can also use the drop-down menu in SPSS, as follows:
From the top menu, click Analyze, then Scale, and then Reliability Analysis.
Transfer variables q1 through q5 into the Items, and leave the model set as Alpha.
In the dialog box, click Statistics.
In the box description, select Item, Scale, and Scale if item deleted. In the inter-item box, select Correlation.
Click Continue and then OK to generate the output.
To interpret the output, you can follow the rule of George and Mallery (2003):
> .9 (Excellent), > .8 (Good), > .7 (Acceptable), > .6 (Questionable), > .5(Poor), and < .5 (Unacceptable)
Notes:
Cronbach's alpha reliability coefficient normally ranges between 0 and 1.
The closer the coefficient is to 1.0, the greater is the internal consistency of the items (variables) in the scale.
Cronbach's alpha coefficient increases either as the number of items (variables) increases, or as the average inter-item correlations increase (i.e., when the number of items is held constant).
Oh, and one more thing. Some days ago came to me a student who asked me a question about why SPSS calculates different Alfa-Cronbach's for standardized and und-standardized data. I do not really know if it is legitimate, but often at a university with which I work is checked initially if several different survey-instruments are measuring the same psychological construct checking compliance of the raw results using the alpha method... But I found something interesting. If both correlations and results of factor analysis are identical standardized and und-standardized same data, nevertheless, the results reliability analysis with alpha were (surprisingly) different for standardized and und-standardized same data. Why, since one and the second is based essentially on the same method as covariances (more-or-less)? Well - I learned something here - SPSS uses a newer formula for calculating Alfa, assuming equal variances for the coefficients (http://www-01.ibm.com/support/docview.wss?uid=swg21479940) instead of the "old" formula working on raw variances (https://en.wikipedia.org/wiki/Cronbach%27s_alpha). I think it's a similar problem to that of the partial eta squared signed by SPSS for (about) 11th version as eta squared, which is why I want share with You this "discovery".
Regards
P.S. Of course I know that using mentioned method is a little bit of discussive, but since we talk about it...
Hi
1. The Reliability consists of several measures:
Item alpha reliability and split-half reliability assess the internal consistency of the items in a questionnaire – that is, do the items tend to be measuring much the same thing? Which measure you want to develop?
2. All the above measures refers to the correlation between scores of any data variables, i.e. the correlation between two or more corresponding variables/observations.
3. The calculation of reliability measures can be done in SPSS through the following commands:
Select analysis
then Scale
then Reliability analysis
4. For more details and examples please refer to, pages249-258, Chapter 27 of the book,
Landau, S. and Everitt, B. S.(2004). A Handbook of Statistical analyses using SPSS.
Regards,
Zuhair
Watch this video on Youtube! It is plainly explained.
https://www.youtube.com/watch?v=2gHvHm2SE5s
Dear Rajat
The attached documents are very helpful in calculating the measures.
Regards,
Zuhair
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