Bayesian models as a unified approach to estimate relative risk (or prevalence ratio) in binary and polytomous outcomes.

IF 3.6 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Emerging Themes in Epidemiology Pub Date : 2015-06-20 eCollection Date: 2015-01-01 DOI:10.1186/s12982-015-0030-y

Vanessa Bielefeldt Leotti Torman, Suzi Alves Camey

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引用次数: 22

Abstract

Background: Disadvantages have already been pointed out on the use of odds ratio (OR) as a measure of association for designs such as cohort and cross sectional studies, for which relative risk (RR) or prevalence ratio (PR) are preferable. The model that directly estimates RR or PR and correctly specifies the distribution of the outcome as binomial is the log-binomial model, however, convergence problems occur very often. Robust Poisson regression also estimates these measures but it can produce probabilities greater than 1.

Results: In this paper, the use of Bayesian approach to solve the problem of convergence of the log-binomial model is illustrated. Furthermore, the method is extended to incorporate dependent data, as in cluster clinical trials and studies with multilevel design, and also to analyse polytomous outcomes. Comparisons between methods are made by analysing four data sets.

Conclusions: In all cases analysed, it was observed that Bayesian methods are capable of estimating the measures of interest, always within the correct parametric space of probabilities.

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贝叶斯模型作为一种统一的方法来估计二元和多元预后的相对风险(或患病率)。

背景:在队列和横断面研究等设计中，已经指出了使用优势比(OR)作为关联度量的缺点，相对危险度(RR)或患病率(PR)更可取。直接估计RR或PR并正确指定结果分布为二项的模型是对数二项模型，但其收敛性问题经常出现。稳健泊松回归也估计这些度量，但它可以产生大于1的概率。结果:本文给出了利用贝叶斯方法求解对数-二项模型的收敛性问题。此外，该方法被扩展到合并依赖数据，如在聚类临床试验和多水平设计的研究中，也用于分析多组结果。通过对四个数据集的分析，对不同方法进行了比较。结论:在所有分析的情况下，可以观察到贝叶斯方法能够估计感兴趣的措施，总是在正确的概率参数空间内。

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

Emerging Themes in Epidemiology Medicine-Epidemiology

CiteScore

4.40

自引率

4.30%

发文量

审稿时长

28 weeks

期刊介绍： Emerging Themes in Epidemiology is an open access, peer-reviewed, online journal that aims to promote debate and discussion on practical and theoretical aspects of epidemiology. Combining statistical approaches with an understanding of the biology of disease, epidemiologists seek to elucidate the social, environmental and host factors related to adverse health outcomes. Although research findings from epidemiologic studies abound in traditional public health journals, little publication space is devoted to discussion of the practical and theoretical concepts that underpin them. Because of its immediate impact on public health, an openly accessible forum is needed in the field of epidemiology to foster such discussion.