Obtaining adjusted prevalence ratios from logistic regression models in cross-sectional studies
<p>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 p...
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Format: | Article |
Language: | English |
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Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz
2015-03-01
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Series: | Cadernos de Saúde Pública |
Subjects: | |
Online Access: | http://www.scielosp.org/scielo.php?script=sci_arttext&pid=S0102-311X2015000300487&lng=en&tlng=en |
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author | Leonardo Soares Bastos Raquel de Vasconcellos Carvalhaes de Oliveira Luciane de Souza Velasque |
author_facet | Leonardo Soares Bastos Raquel de Vasconcellos Carvalhaes de Oliveira Luciane de Souza Velasque |
author_sort | Leonardo Soares Bastos |
collection | DOAJ |
description | <p>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.</p> |
first_indexed | 2024-12-21T10:59:31Z |
format | Article |
id | doaj.art-c0c27ba3ddd14b9b8cd64e7369fe5261 |
institution | Directory Open Access Journal |
issn | 0102-311X |
language | English |
last_indexed | 2024-12-21T10:59:31Z |
publishDate | 2015-03-01 |
publisher | Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz |
record_format | Article |
series | Cadernos de Saúde Pública |
spelling | doaj.art-c0c27ba3ddd14b9b8cd64e7369fe52612022-12-21T19:06:24ZengEscola Nacional de Saúde Pública, Fundação Oswaldo CruzCadernos de Saúde Pública0102-311X2015-03-0131348749510.1590/0102-311X00175413S0102-311X2015000300487Obtaining adjusted prevalence ratios from logistic regression models in cross-sectional studiesLeonardo Soares BastosRaquel de Vasconcellos Carvalhaes de OliveiraLuciane de Souza Velasque<p>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.</p>http://www.scielosp.org/scielo.php?script=sci_arttext&pid=S0102-311X2015000300487&lng=en&tlng=enRazón de PrevalenciasModelos LogísticosEstudios Transversales |
spellingShingle | Leonardo Soares Bastos Raquel de Vasconcellos Carvalhaes de Oliveira Luciane de Souza Velasque Obtaining adjusted prevalence ratios from logistic regression models in cross-sectional studies Cadernos de Saúde Pública Razón de Prevalencias Modelos Logísticos Estudios Transversales |
title | Obtaining adjusted prevalence ratios from logistic regression models in cross-sectional studies |
title_full | Obtaining adjusted prevalence ratios from logistic regression models in cross-sectional studies |
title_fullStr | Obtaining adjusted prevalence ratios from logistic regression models in cross-sectional studies |
title_full_unstemmed | Obtaining adjusted prevalence ratios from logistic regression models in cross-sectional studies |
title_short | Obtaining adjusted prevalence ratios from logistic regression models in cross-sectional studies |
title_sort | obtaining adjusted prevalence ratios from logistic regression models in cross sectional studies |
topic | Razón de Prevalencias Modelos Logísticos Estudios Transversales |
url | http://www.scielosp.org/scielo.php?script=sci_arttext&pid=S0102-311X2015000300487&lng=en&tlng=en |
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