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st: Why do Stata Cronbach's Alpha values not match SAS?
From
"Gramig, Benjamin M" <[email protected]>
To
"[email protected]" <[email protected]>
Subject
st: Why do Stata Cronbach's Alpha values not match SAS?
Date
Wed, 27 Apr 2011 19:54:16 -0400
I have used the alpha, item- command in Stata to calculate Cronbachs alpha to evaluate scale reliability of a group of Likert scale survey questions and received the following Stata output:
. alpha natural anthropogenic no_affect_farm warming_will_help invented extreme media policies, item
Test scale = mean(unstandardized items)
average
item-test item-rest interitem
Item | Obs Sign correlation correlation covariance alpha
-------------+-----------------------------------------------------------------
natural | 749 + 0.4101 0.2291 .3454548 0.7859
anthropoge~c | 749 - 0.7044 0.5677 .272278 0.7317
no_affect_~m | 747 + 0.5445 0.3748 .3167923 0.7673
warming_wi~p | 747 + 0.3860 0.2371 .3544383 0.7820
invented | 742 + 0.7862 0.6657 .2435609 0.7093
extreme | 747 - 0.6441 0.5121 .2954857 0.7436
media | 747 + 0.7563 0.6447 .2611056 0.7156
policies | 746 + 0.6400 0.5080 .2948471 0.7421
-------------+-----------------------------------------------------------------
Test scale | .2979834 0.7737
-------------------------------------------------------------------------------
When I attempt to use SAS to calculate the same Alpha reliability value using the –PROC CORR data alpha- command I get much lower values (pasted below) for items in the scale as well as the overall alpha for the entire scale. The qualitative results in terms of sign and relative magnitude of alphas calculated when removing individual items from the scale are consistent with Stata, but not the magnitudes. I have read the manuals for both pieces of software and it is not clear to me that there are differences in what is being reported by both software packages.
Has anyone else encountered this drastic difference? I assume that there is something systematically different about what is going on in the two packages to calculate the reported values, but I couldn’t determine what this difference was.
It should be noted that I turned to SAS to be able to use polychoric correlations in a PCA with a full set of diagnostics, outputs and rotations available. This seems necessary for my ordinal data, despite ignoring this in the comparison of alpha calculations shared here. I did explore
-polychoricpca- in Stata before deciding to use SAS.
Any insights are greatly appreciated,
Ben
******SAS output**************
Cronbach Coefficient Alpha
Variables Alpha
Raw 0.21871
Standardized 0.230030
Cronbach Coefficient Alpha with Deleted Variable
Raw Variables Standardized Variables
Deleted Correlation Correlation
Variable with Total Alpha with Total Alpha Label
natural 0.272378 0.069753 0.270229 0.082498 natural
anthropogenic -.422341 0.495123 -.400057 0.472209 anthropogenic
no_affect_farm 0.239609 0.085832 0.239147 0.104634 no_affect_farm
warming_will_help0.165372 0.154351 0.160833 0.158495 warming_will_help
invented 0.271282 0.038784 0.283484 0.072925 invented
extreme -.340953 0.424482 -.339788 0.443982 extreme
media 0.389877 -.032350 0.373906 0.005444 media
policies 0.355568 0.016073 0.335595 0.034502 policies
------------------
Benjamin M. Gramig
Assistant Professor
Dept. of Agricultural Economics
Purdue University
[email protected]
http://web.ics.purdue.edu/~bgramig/
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