  This paper is motivated by a Eurobarometer survey on science knowledge. As
part of the survey, respondents were asked to rank sources of science
information in order of importance. The official statistical analysis of these
data however failed to use the complete ranking information. We instead propose
a method which treats ranked data as a set of paired comparisons which places
the problem in the standard framework of generalized linear models and also
allows respondent covariates to be incorporated. An extension is proposed to
allow for heterogeneity in the ranked responses. The resulting model uses a
nonparametric formulation of the random effects structure, fitted using the EM
algorithm. Each mass point is multivalued, with a parameter for each item. The
resultant model is equivalent to a covariate latent class model, where the
latent class profiles are provided by the mass point components and the
covariates act on the class profiles. This provides an alternative
interpretation of the fitted model. The approach is also suitable for paired
comparison data.
