Biclustering models for two-mode ordinal data

The work in this paper introduces finite mixture models that can be used to simul-

taneously cluster the rows and columns of two-mode ordinal categorical response data,

such as those resulting from Likert scale responses. We use the popular proportional

odds parameterisation and propose models which provide insights into major patterns

in the data. Model-fitting is performed using the EM algorithm and a fuzzy allocation

of rows and columns to corresponding clusters is obtained. The clustering ability of the

models is evaluated in a simulation study and demonstrated using two real data sets.