The Collaborative Perinatal Project is a large study aimed at identifying the risks and complications of pregnancies. Data about the pregnancy and the birth outcome were collected on a large number of women from 12 different hospitals over several years. We focus on the duration of the pregnancy, and we investigate the heterogeneity of the gestational age among women and between hospitals. We apply a hierarchical mixture model based on the thinned dependent Dirichlet process of [2], and we show how this approach is able to simultaneously convey a clustering of patients and hospitals.

D'Angelo, L., Nipoti, B., Ongaro, A. (2025). Two-Level Clustering of Patients and Hospitals via Thinned Dependent Dirichlet Process Mixtures. In A. Pollice, P. Mariani (a cura di), Methodological and Applied Statistics and Demography II SIS 2024, Short Papers, Solicited Sessions (pp. 37-42). Springer [10.1007/978-3-031-64350-7_7].

Two-Level Clustering of Patients and Hospitals via Thinned Dependent Dirichlet Process Mixtures

D'Angelo, Laura
;
Nipoti, Bernardo;Ongaro, Andrea
2025

Abstract

The Collaborative Perinatal Project is a large study aimed at identifying the risks and complications of pregnancies. Data about the pregnancy and the birth outcome were collected on a large number of women from 12 different hospitals over several years. We focus on the duration of the pregnancy, and we investigate the heterogeneity of the gestational age among women and between hospitals. We apply a hierarchical mixture model based on the thinned dependent Dirichlet process of [2], and we show how this approach is able to simultaneously convey a clustering of patients and hospitals.
Capitolo o saggio
Bayesian nonparametrics; model-based clustering; nested data
English
Methodological and Applied Statistics and Demography II SIS 2024, Short Papers, Solicited Sessions
Pollice, A; Mariani, P
3-mar-2025
2025
9783031643491
Springer
37
42
D'Angelo, L., Nipoti, B., Ongaro, A. (2025). Two-Level Clustering of Patients and Hospitals via Thinned Dependent Dirichlet Process Mixtures. In A. Pollice, P. Mariani (a cura di), Methodological and Applied Statistics and Demography II SIS 2024, Short Papers, Solicited Sessions (pp. 37-42). Springer [10.1007/978-3-031-64350-7_7].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/548009
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