前瞻性研究非独立性二分类结局的Poisson回归方法

doi:10.3969/j.issn.1006-5253.2022.05.016

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摘要

目的基于SAS软件结合修正Poisson回归方法分析非独立性前瞻性数据。方法通过实例，比较常见方法和非独立Poisson回归法分析观察性研究的性能，并运用SAS软件分析数据。结果以普通Poisson回归法为标准参照，logistic回归得到的OR值明显偏离真实的RR值，非独立Poisson回归的RR区间估计最为精确。结论非独立Poisson回归法更适合于处理常见结局事件的非独立性前瞻性研究资料。

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	王俊苹
	沈灵智
	卢肇骏
	寇硕
	郑卫军

关键词 ： Poisson回归, 非独立性数据, RR值, SAS软件

Abstract：

Objective To analyze non-independent prospective data based on SAS software combined with modified Poisson regression.Methods The cluster data of observational studies were analyzed by comparing common methods and modified central effect Poisson regression analysis with SAS software.Results According to the standard of general Poisson regression, the OR-value obtained by logistic regression deviates from the real RR-value, and the modified central effect Poisson regression is more accurate.Conclusion Modified central effect Poisson regression model is more suitable for the treatment of common outcome events of non-independent prospective research data.

Key words： Poisson regression non-independent data relative risk SAS software

收稿日期: 2022-07-24

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通讯作者: 郑卫军，Email：deardangjun@163.com

引用本文:

王俊苹，沈灵智，卢肇骏，寇硕，郑卫军. 前瞻性研究非独立性二分类结局的Poisson回归方法[J]. 中国医院统计, 2022, 29(5): 397-400.
Wang Junping，Shen Lingzhi，Lu Zhaojun，Kou Shuo，Zheng Weijun. Prospective study of non-independent binary classification by Poisson regression. journal1, 2022, 29(5): 397-400.

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