Bayesian Hierarchical Model for Evaluating Risk Reduction in District Hospitals Systems in South Africa
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| Natura: | Recurso digital |
| Lingua: | inglese |
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Zenodo
2014
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| _version_ | 1866901613864550400 |
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| author | Young, Simon Smith, Natalie |
| author_facet | Young, Simon Smith, Natalie |
| contents | <p>This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in South Africa: Bayesian hierarchical model for measuring risk reduction in South Africa. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of district hospitals systems in South Africa: Bayesian hierarchical model for measuring risk reduction, South Africa, Africa, Medicine, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19033214 |
| institution | Zenodo |
| language | eng |
| publishDate | 2014 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Bayesian Hierarchical Model for Evaluating Risk Reduction in District Hospitals Systems in South Africa Young, Simon Smith, Natalie Sub-Saharan African Bayesian Modelling Hierarchical Quantitative Epidemiology <p>This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in South Africa: Bayesian hierarchical model for measuring risk reduction in South Africa. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of district hospitals systems in South Africa: Bayesian hierarchical model for measuring risk reduction, South Africa, Africa, Medicine, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.</p> |
| title | Bayesian Hierarchical Model for Evaluating Risk Reduction in District Hospitals Systems in South Africa |
| topic | Sub-Saharan African Bayesian Modelling Hierarchical Quantitative Epidemiology |
| url | https://doi.org/10.5281/zenodo.19033214 |