Abstract
Multidimensional phenomena are often characterised by nested latent concepts ordered in a hierarchical structure, from the most specific to the most general
ones. In this paper, we model a nonnegative data covariance matrix by extending the
Ultrametric Correlation Model to covariance matrices. The proposal is a parsimonious model which identifies a partition of variables in a reduced number of groups,
and the relationships among them via the ultrametric property. The proposed model
is applied to investigate the relationships among the dimensions of the Teachers’
Job Satisfaction in Italian secondary schools.
ones. In this paper, we model a nonnegative data covariance matrix by extending the
Ultrametric Correlation Model to covariance matrices. The proposal is a parsimonious model which identifies a partition of variables in a reduced number of groups,
and the relationships among them via the ultrametric property. The proposed model
is applied to investigate the relationships among the dimensions of the Teachers’
Job Satisfaction in Italian secondary schools.
| Original language | English |
|---|---|
| Title of host publication | Book of Short Papers SIS 2021 |
| Pages | 1319-1324 |
| Publication status | Published - 2021 |
| Event | SIS2021 - PISA, Italy Duration: 21 Jun 2021 → 25 Jun 2021 |
Conference
| Conference | SIS2021 |
|---|---|
| Country/Territory | Italy |
| City | PISA |
| Period | 21/06/21 → 25/06/21 |