Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/244441 
Year of Publication: 
2008
Series/Report no.: 
Working Paper No. 6/2008
Publisher: 
Örebro University School of Business, Örebro
Abstract: 
Rating scales for outcome variables produce categorical data which are often ordered and measurements from rating scales are not standardized. The purpose of this study is to apply commonly used and novel methods for paired ordered categorical data to two data sets with different properties and to compare the results and the conditions for use of these models. The two applications consist of a data set of inter-rater reliability and a data set from a follow-up evaluation of patients. Standard measures of agreement and measures of association are used. Various loglinear models for paired categorical data using properties of quasi-independence and quasi-symmetry as well as logit models with a marginal modelling approach are used. A nonparametric method for ranking and analyzing paired ordered categorical data is also used. We show that a deeper insight when it comes to disagreement and change patterns may be reached using the nonparametric method and illustrate some problems with standard measures as well as parametric loglinear and logit models. In addition, the merits of the nonparametric method are illustrated.
Subjects: 
Agreement:ordinal data
ranking
reliability
rating scales
JEL: 
C14
Document Type: 
Working Paper

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