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Re: st: Interrater agreement: finding the problematic items Date

From   "Lacy,Michael" <>
To   "" <>
Subject   Re: st: Interrater agreement: finding the problematic items Date
Date   Fri, 14 Jun 2013 20:57:58 +0000

Ilian, Henry (ACS)" <> wrote:

>I'm doing an interrater agreement study on a case-reading instrument. There are five reviewers using an instrument with 120 items.
>The ratings scales are ordinal with either two, three or four options. I'm less interested in reviewer tendencies than I am in
>problematic items, those with high levels of disagreement.
>Most of the interrater agreement/interrater reliability statistics look at reviewer tendencies. I can see two ways of getting at
>agreement on items. The first is to sum all the differences between all possible pairs of reviewers, and those with the highest
>totals are the ones to examine. The other is Chronbach's alpha. Is there any strong argument for or against either approach, and is
>there a different approach that would be better than these?

My package -ordvar- (self-promotion mode on) might be of some use to you here.  
In your case, it would provide a 0/1 measure of the dispersion of each item's 
rating distribution.   Although not implemented in that package, an essentially 
identical measure (IOV) that may be better suited to data with small frequencies 
of raters is also cited in the help for that package.  

package ordvar from

      'ORDVAR': module to calculate measures of ordinal consensus and dispersion

      ordvar calculates measures of ordinal consensus  and dispersion.
      These include lsq and 1-lsq, which are 0/1 normed ordinal
      consensus and  dispersion statistics described in Blair and Lacy
      (2000). [detailed citation

 Blair, J. and M. Lacy. 2000. "Statistics of Ordinal Variation." Sociological Methods and Research. 28: 251-280
 Berry, K. J. and P. W. Mielke, Jr. 1992. "Assessment of Variation in Ordinal Data." Perceptual and Motor Skills

I also would suggest looking at Richard William's -oglm-.  It estimates location-scale ordinal response models,
However, I don't know how well estimates from a regression model like that would perform with only
5 reviewers.


Mike Lacy
Dept. of Sociology
Colorado State University
Fort Collins CO 80523-1784

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