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一种用于二元数据前瞻性研究的修正泊松回归方法。

A modified poisson regression approach to prospective studies with binary data.

作者信息

Zou Guangyong

机构信息

Robarts Clinical Trials, Robarts Research Institute, London, Ontario, Canada.

出版信息

Am J Epidemiol. 2004 Apr 1;159(7):702-6. doi: 10.1093/aje/kwh090.

DOI:10.1093/aje/kwh090
PMID:15033648
Abstract

Relative risk is usually the parameter of interest in epidemiologic and medical studies. In this paper, the author proposes a modified Poisson regression approach (i.e., Poisson regression with a robust error variance) to estimate this effect measure directly. A simple 2-by-2 table is used to justify the validity of this approach. Results from a limited simulation study indicate that this approach is very reliable even with total sample sizes as small as 100. The method is illustrated with two data sets.

摘要

相对风险通常是流行病学和医学研究中感兴趣的参数。在本文中,作者提出了一种改进的泊松回归方法(即具有稳健误差方差的泊松回归)来直接估计这种效应量度。使用一个简单的2×2表格来证明该方法的有效性。一项有限的模拟研究结果表明,即使总样本量小至100,该方法也非常可靠。用两个数据集对该方法进行了说明。

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