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.
Clustering Upper Level Units in Multilevel Models for Ordinal Data / Grilli, Leonardo; Panzera, Agnese; Rampichini, Carla. - STAMPA. - (2018), pp. 137-144. [10.1007/978-3-319-55708-3_15]
Titolo: | Clustering Upper Level Units in Multilevel Models for Ordinal Data | |
Autori di Ateneo: | ||
Autori: | Grilli, Leonardo; Panzera, Agnese; Rampichini, Carla | |
Anno di registrazione: | 2018 | |
Titolo del libro: | Classification, (Big) Data Analysis and Statistical Learning | |
ISBN: | 978-3-319-55707-6 978-3-319-55708-3 | |
Serie: | ||
Pagina iniziale: | 137 | |
Pagina finale: | 144 | |
Abstract: | 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. | |
Handle: | http://hdl.handle.net/2158/1113338 | |
Appare nelle tipologie: | 2a - Art/Cap/Saggio libro scient/tech |
File in questo prodotto:
File | Descrizione | Tipologia | Licenza | |
---|---|---|---|---|
Clustering multilevel ordinal - Grilli Panzera Rampichini 2018.pdf | articolo principale | Versione finale referata (Postprint, Accepted manuscript) | DRM non definito | Administrator Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.