Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
From | "Gramig, Benjamin M" <bgramig@purdue.edu> |
To | "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |
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 bgramig@purdue.edu http://web.ics.purdue.edu/~bgramig/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/