Orellana Juan J, Kaufman Jay S, Pino Paulina
Departamento de Salud Pública, Facultad de Medicina, universidad de la frontera, Temuco, Chile.
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Quebec, Canada.
Rev Peru Med Exp Salud Publica. 2013 Oct-Dec;30(4):687-90.
In public health there is a growing appreciation for the advantage of the additive scale to better understand the impacts of factors involved in a health event. It is necessary to always remember that the concept of statistical interaction is scale dependent. In the causal relationship between a response and the presence of two or more factors, the concepts interaction, synergy and antagonism are the key ideas. The aim of this note is to show an application of the concepts interaction, synergy and antagonism in prospective studies from a public health perspective. We present three scenarios that illustrate analyses of interaction, independence, synergy and antagonism. Stata 12 software was used for fitting models (log-binomial model and Poisson) and estimating parameters. Appendixes are provided with concepts and Stata commands used in the processes of simulation and parameter estimation.
在公共卫生领域，人们越来越认识到加性量表在更好地理解健康事件中所涉及因素的影响方面的优势。必须始终牢记，统计交互作用的概念取决于量表。在一个反应与两个或更多因素的存在之间的因果关系中，交互作用、协同作用和拮抗作用的概念是关键要点。本笔记的目的是从公共卫生角度展示交互作用、协同作用和拮抗作用概念在前瞻性研究中的应用。我们呈现了三个场景，用以说明对交互作用、独立性、协同作用和拮抗作用的分析。使用Stata 12软件拟合模型（对数二项式模型和泊松模型）并估计参数。附录中提供了模拟和参数估计过程中使用的概念及Stata命令。
