Derivation of the linear-logistic model and Cox's proportional hazard model from a canonical system description.
Derivation of the linear-logistic model and Cox's proportional hazard model from a canonical system description.
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从规范系统描述推导线性逻辑模型和 Cox 比例风险模型。
DOI：
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发表时间：
1997
影响因子：
2
通讯作者：
Rebecca G. Knapp
中科院分区：
文献类型：
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作者：
Eberhard O. Voit;Rebecca G. Knapp
线性逻辑回归模型和Cox比例风险模型在流行病学中广泛应用。它们的成功应用毫无疑问地表明它们准确反映了观察到的疾病过程及其相关风险或发病率。尽管它们很突出，但这些模型为何有效并不清楚。本文介绍了这两个模型从规范建模框架中的推导。它首先对风险源和疾病发展之间的动态进行一般描述，在 S 系统的规范表示中制定这种描述，并展示线性逻辑模型和 Cox 比例风险模型如何自然地从这种表示中得出。本文根据流行病学概念和一般系统理论解释了模型参数，并解释了这些流行病学模型应用中普遍接受的假设和局限性。
The linear-logistic regression model and Cox's proportional hazard model are widely used in epidemiology. Their successful application leaves no doubt that they are accurate reflections of observed disease processes and their associated risks or incidence rates. In spite of their prominence, it is not a priori evident why these models work. This article presents a derivation of the two models from the framework of canonical modeling. It begins with a general description of the dynamics between risk sources and disease development, formulates this description in the canonical representation of an S-system, and shows how the linear-logistic model and Cox's proportional hazard model follow naturally from this representation. The article interprets the model parameters in terms of epidemiological concepts as well as in terms of general systems theory and explains the assumptions and limitations generally accepted in the application of these epidemiological models.