Clustering Upper Level Units in Multilevel Models for Ordinal Data

We consider an explorative method for unsupervised clustering of upper level units in a two-level hierarchical setting. The idea lies in applying a density-based clustering algorithm to the predicted random effects obtained from a multilevel cumulative logit model. We illustrate the proposed approach throughout the analysis of data from European Social Survey about political trust in European countries.

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