Influence Diagnostics for Correlated Binomial Regression Models: An Application to a Data Set on High-Cost Health Services Occurrence
DOI10.15446/rce.v44n2.85606zbMath1480.62154OpenAlexW3205740709MaRDI QIDQ5029403
Carlos Alberto Ribeiro Diniz, Rubiane M. Pires, Paulo H. Ferreira, Carolina Costa Mota Paraíba
Publication date: 14 February 2022
Published in: Revista Colombiana de Estadística (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.15446/rce.v44n2.85606
Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12) Diagnostics, and linear inference and regression (62J20)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Bayesian analysis of a correlated binomial model
- Correlated binomial regression models
- A family of partially correlated Poisson models for overdispersion
- Case-deletion measures for models with incomplete data
- Outlier Detection Using Nonconvex Penalized Regression
- Spatial Statistics and Spatio‐Temporal Data
- Binary Regression Using an Extended Beta-Binomial Distribution, With Discussion of Correlation Induced by Covariate Measurement Errors
- A generalization of the binomial distribution
This page was built for publication: Influence Diagnostics for Correlated Binomial Regression Models: An Application to a Data Set on High-Cost Health Services Occurrence