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通过逻辑回归从病例对照数据估计归因风险。

Attributable risk estimation from case-control data via logistic regression.

作者信息

Drescher K, Schill W

机构信息

Institute of Statistics, University of Bremen, Germany.

出版信息

Biometrics. 1991 Dec;47(4):1247-56.

PMID:1786317
Abstract

By fitting an unconditional logistic regression model to unmatched case-control data, an estimate of the joint population attributable risk for the factor included is obtained. This estimate and its asymptotic variance can easily be computed from the intercept parameter and its asymptotic variance. A generalization to the analysis of stratified data with large strata enables the calculation of stratum-specific attributable risks and their variances via stratum-specific intercept parameters. If sampling of cases is independent of strata, an estimate of the summary attributable risk and its asymptotic variance may be obtained as a weighted sum of the stratum-specific attributable risks.

摘要

通过对未匹配的病例对照数据拟合无条件逻辑回归模型,可以获得所纳入因素的联合人群归因风险估计值。该估计值及其渐近方差可根据截距参数及其渐近方差轻松计算得出。对具有大分层的分层数据进行分析的一种推广方法,能够通过特定分层的截距参数计算特定分层的归因风险及其方差。如果病例抽样与分层无关,则汇总归因风险估计值及其渐近方差可作为特定分层归因风险的加权和来获得。

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