Cadernos de Saúde Pública | |
Obtaining adjusted prevalence ratios from logistic regression models in cross-sectional studies | |
Leonardo Soares Bastos1  Raquel De Vasconcellos Carvalhaes De Oliveira1  Luciane De Souza Velasque1  | |
关键词: Prevalence Ratio; Logistic Models; Cross-Sectional Studies; Razão de Prevalências; Modelos Logísticos; Estudos Transversais; Razón de Prevalencias; Modelos Logísticos; Estudios Transversales; | |
DOI : 10.1590/0102-311X00175413 | |
来源: SciELO | |
【 摘 要 】
In the last decades, the use of the epidemiological prevalence ratio (PR) instead of the odds ratio has been debated as a measure of association in cross-sectional studies. This article addresses the main difficulties in the use of statistical models for the calculation of PR: convergence problems, availability of tools and inappropriate assumptions. We implement the direct approach to estimate the PR from binary regression models based on two methods proposed by Wilcosky & Chambless and compare with different methods. We used three examples and compared the crude and adjusted estimate of PR, with the estimates obtained by use of log-binomial, Poisson regression and the prevalence odds ratio (POR). PRs obtained from the direct approach resulted in values close enough to those obtained by log-binomial and Poisson, while the POR overestimated the PR. The model implemented here showed the following advantages: no numerical instability; assumes adequate probability distribution and, is available through the R statistical package.
【 授权许可】
CC BY
All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
RO202005130091904ZK.pdf | 237KB | download |