A general conceptual and statistical framework to model non-linear and delayed exposure-response relationships and combi

评估各种风险因素对健康影响的科学研究通常依赖于统计模型，该模型用于量化人们接触的剂量与健康结果之间的关系。这种关系应该简明扼要和可靠地总结这种联系，以便正确地告知特定危险因素的健康后果。这种关联性通常是在多个可比较的研究中估计的，然后需要将这些证据结合起来，以提高对相关健康风险的了解。伦敦卫生与热带医学院的研究人员与MRC-Cambridge和南加州大学合作，推动了一个项目，提供适合描述复杂关系的统计工具，并在研究中将它们结合起来。这些方法将在统计软件中实施，供在不同生物医学领域工作的所有研究人员免费使用。该项目的目的是改进分析方法，以研究风险因素与人类健康之间的关联。

Scientific studies which assess the health effects of various risk factors usually depend on statistical models, used to quantify the relationship between the dose people are exposed to, and the health outcome. This relationship should concisely and reliably summarize the association, in order to correctly inform about the health consequences of specific risk factors. This association is usually estimated in multiple comparable studies, whose evidence needs then to be combined in order to improve the knowledge about related health risks.Researchers at the London School of Hygiene and Tropical Medicine, in collaboration with the MRC-Cambridge and the University of Southern California, have promoted a project to provide the statistical tools suitable to describe complex relationships and combine them across studies. These methodologies will be implemented in statistical software, freely available and usable by all the researchers working in different biomedical fields. The aim of the project is to improve the analytical method to study the association between risk factors and human health.