We consider the issue of clustering upper level units in hierarchical data with an ordinal response. An example is the clustering of university courses (level 2 units) on the basis of the ratings expressed by students (level 1 units) using an ordinal scale, with the aim of identifying ‘good’ and ‘bad’ courses. Another example is the clustering of European regions on the basis of individual satisfaction levels on a Likert scale. In this framework, model-based clustering can be achieved by fitting multilevel models for ordinal data and then exploiting the predicted random effects.
Clustering upper level units in multilevel models for ordinal data / Leonardo Grilli, Agnese Panzera, Carla Rampichini. - STAMPA. - (2015), pp. 288-290. (Intervento presentato al convegno CLADAG 2015).
Clustering upper level units in multilevel models for ordinal data
Leonardo Grilli;Agnese Panzera;Carla Rampichini
2015
Abstract
We consider the issue of clustering upper level units in hierarchical data with an ordinal response. An example is the clustering of university courses (level 2 units) on the basis of the ratings expressed by students (level 1 units) using an ordinal scale, with the aim of identifying ‘good’ and ‘bad’ courses. Another example is the clustering of European regions on the basis of individual satisfaction levels on a Likert scale. In this framework, model-based clustering can be achieved by fitting multilevel models for ordinal data and then exploiting the predicted random effects.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.