Analyzing health care data using count models: A novel approach to Length of Stay analysis
Fuente:
arXiv
Salvato in:
| Autori principali: | , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866912568562417664 |
|---|---|
| author | Ahmad, Peer Bilal Elah, Na |
| author_facet | Ahmad, Peer Bilal Elah, Na |
| contents | Count data modeling has been extensively applied in medical sciences to analyze various healthcare datasets. Numerous probability models have been developed to address diverse aspects of healthcare data. In this study, we propose a novel count data model for analyzing healthcare datasets. Key structural properties of the model are established, and an associated regression framework is introduced to examine the effects of various covariates. Additionally, a three-inflated distribution, based on the proposed model, is presented to analyze length of stay of patients in hospitals. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_02703 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Analyzing health care data using count models: A novel approach to Length of Stay analysis Ahmad, Peer Bilal Elah, Na Methodology 60E05, 62F03, 62J05, 62P10 Count data modeling has been extensively applied in medical sciences to analyze various healthcare datasets. Numerous probability models have been developed to address diverse aspects of healthcare data. In this study, we propose a novel count data model for analyzing healthcare datasets. Key structural properties of the model are established, and an associated regression framework is introduced to examine the effects of various covariates. Additionally, a three-inflated distribution, based on the proposed model, is presented to analyze length of stay of patients in hospitals. |
| title | Analyzing health care data using count models: A novel approach to Length of Stay analysis |
| topic | Methodology 60E05, 62F03, 62J05, 62P10 |
| url | https://arxiv.org/abs/2509.02703 |