Regressions applied to the study of discrete events in epidemiology
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Keywords

Generalized Lineal Models
Poisson Regression
Binomial Regression
Incidence Rate Ratio
Relative Risk
Prevalence Ratio

How to Cite

Diaz Quijano, F. A. (2016). Regressions applied to the study of discrete events in epidemiology. Salud UIS, 48(1). https://doi.org/10.18273/revsal.v48n1-2016001

Abstract

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.

https://doi.org/10.18273/revsal.v48n1-2016001
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