Re: Shapiro-Wilks Statistic

Posted by Baker, Harley on
URL: http://spssx-discussion.165.s1.nabble.com/Shapiro-Wilks-Statistic-tp5739693p5739710.html

Thanks, Art

Polychoric correlations provide exactly what I need, as the EFA is the first step in a longer process (produce factor scores for use in the next phases of the analyses, etc.) The reviewer just wanted - I hope - some confirmation that the data were not suitable for Pearson r at the univariate level beyond the skew and kurtosis values that were all highly statistically signifiant with associated strong effect sizes. So the data don't fit Pearson assumptions likely due to the categorization imposed by the response format, but they nicely fit the assumptions/requirements for polychoric correlations to estimate the real correlations among them (e.g.Holgado-Tello, F. P., Chacón-Moscoso, S., Barbero-García, I., & Vila-Abad, E. (2010). Polychoric versus Pearson correlations in exploratory and confirmatory factor analysis of ordinal variables. Quality & Quantity: International Journal of Methodology, 44(1), 153–166.)

 
Harley

Dr. Harley Baker
Professor Emeritus of Psychology
California State University Channel Islands
One University Drive
Camarillo, CA 93012
 


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You said you had ordinal data.  When I have reviewed manuscripts where other
reviewers have raised the issue of level of measurement this is what I have
suggested.
Try CATREG in SPSS.  CATREG does a test between models with different
assumptions about measurement level. See whether there is a meaningful
difference between MODEL fits with  ORDINAL specification and INTERVAL
specifications.  (You might also try a NOMINAL specification.)
If there is no meaningful difference in fits, use the interval level results
and add a footnote that CATREG showed no meaningful difference in fits when
ORDINAL was specified.



YMMV but I have tried this CATREG approach a dozen or so times and never
found a meaningful difference between the fits.

also see CATPCA in help



-----
Art Kendall
Social Research Consultants
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