Regresiones aplicadas al estudio de eventos discretos en epidemiología

Some basic aspects about using regressions in epidemiological studies are reviewed. Particularly, this manuscript focused on those applied to the study of discrete events. Generalized lineal models, such as Poisson and log-binomial, have a structure that is an extension of a lineal equation to analyze discrete outcomes. Thus, we can estimate association measures as the incidence rate ratio, using the Poisson regression, or the relative risk (or prevalence ratio), using log-binomial regression. In each case it is essential to know the nature of the dependent variable, as well as, its distribution and recognize the limitations of each analysis tool.

• Fecha de publicación: 2016
• Institución: Universidad Industrial de Santander
• Repositorio: Repositorio UIS
• Idioma: spa
• OAI Identifier: oai:noesis.uis.edu.co:20.500.14071/8836
• Acceso en línea: https://revistas.uis.edu.co/index.php/revistasaluduis/article/view/5397; https://noesis.uis.edu.co/handle/20.500.14071/8836
• Palabra clave: Generalized Lineal Models; Poisson Regression; Binomial Regression; Incidence Rate Ratio; Relative Risk; Prevalence Ratio; Modelos lineales generalizados; Regresión de Poisson; Regresión Binomial; Razón de tasas; Riesgo Relativo; Razón de Prevalencias
• Rights: openAccess
• License: Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)