LOGISTIC DISEASE INCIDENCE MODELS AND CASE-CONTROL STUDIES
LOGISTIC DISEASE INCIDENCE MODELS AND CASE-CONTROL STUDIES
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DOI：
10.1093/biomet/66.3.403
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发表时间：
1979-01-01
期刊：
影响因子：
2.7
通讯作者：
PYKE, R
中科院分区：
文献类型：
--
作者：
PRENTICE, RL;PYKE, R
通过对数回归模型描述特定时间段内疾病发生的概率。在给定疾病状态的情况下，归纳回归变量模型并将其应用于病例对照数据。优势比估计量和渐近方差矩阵可以通过将原始对数回归模型应用于病例对照研究来获得，就像在前瞻性研究中获得数据一样。这一结果为一系列分层规模相当大的病例对照研究提供了灵活方便的分析方法。这项工作扩展了 Anderson (1972) 关于对数歧视的结果，并概括了 Breslow et Powers (1978) 关于当前瞻性和回顾性对数模型应用于病例对照数据时优势比估计量的等效性的发现。
The probability of disease development in a defined time period is described by a log regression model. A model for the regression variable, given disease status, is induced and is applied to case control data. The odds ratio estimators and the asymptotic variance matrices may be obtained by applying the original log regression model to the case control study as if the data are obtained in a prospective study. This result gives a flexible and convenient method of analysis for a range of case control studies in which stratum sizes are reasonably large. The work extends Anderson''s (1972) results on log discrimination and generalizes the findings of Breslow et Powers (1978) on the equivalence of odds ratio estimators when both prospective and retrospective log models are applied to case control data.