Poisson excess relative risk models: New implementations and software

IF 0.7 4区数学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Sort-Statistics and Operations Research Transactions Pub Date : 2018-12-21 DOI:10.2436/20.8080.02.76

M. Higueras, A. Howes

引用次数: 0

Abstract

Two new implementations for fitting Poisson excess relative risk methods are proposed for as- sumed simple models. This allows for estimation of the excess relative risk associated with a unique exposure, where the background risk is modelled by a unique categorical variable, for example gender or attained age levels. Additionally, it is shown how to fit general Poisson linear relative risk models in R. Both simple methods and the R fitting are illustrated in three examples. The first two examples are from the radiation epidemiology literature. Data in the third example are randomly generated with the purpose of sharing it jointly with the R scripts.

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泊松超额相对风险模型:新的实现和软件

提出了两种拟合泊松超额相对风险方法的新实现。这样就可以估计与独特暴露相关的过量相对风险，其中背景风险由独特的分类变量建模，例如性别或达到的年龄水平。此外，本文还展示了如何在R中拟合一般泊松线性相对风险模型。通过三个例子说明了简单方法和R拟合。前两个例子来自辐射流行病学文献。第三个示例中的数据是随机生成的，目的是与R脚本共享。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Sort-Statistics and Operations Research Transactions 管理科学-统计学与概率论

CiteScore

3.10

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： SORT (Statistics and Operations Research Transactions) —formerly Qüestiió— is an international journal launched in 2003. It is published twice-yearly, in English, by the Statistical Institute of Catalonia (Idescat). The journal is co-edited by the Universitat Politècnica de Catalunya, Universitat de Barcelona, Universitat Autonòma de Barcelona, Universitat de Girona, Universitat Pompeu Fabra i Universitat de Lleida, with the co-operation of the Spanish Section of the International Biometric Society and the Catalan Statistical Society. SORT promotes the publication of original articles of a methodological or applied nature or motivated by an applied problem in statistics, operations research, official statistics or biometrics as well as book reviews. We encourage authors to include an example of a real data set in their manuscripts.