Prevalence ratio estimation via logistic regression: a tool in R

An Acad Bras Cienc. 2021 Sep 17;93(4):e20190316. doi: 10.1590/0001-3765202120190316. eCollection 2021.

Abstract

The interpretation of odds ratios (OR) as prevalence ratios (PR) in cross-sectional studies have been criticized since this equivalence is not true unless under specific circumstances. The logistic regression model is a very well known statistical tool for analysis of binary outcomes and frequently used to obtain adjusted OR. Here, we introduce the prLogistic for the R statistical computing environment which can be obtained from The Comprehensive R Archive Network, https://cran.r-project.org/package=prLogistic. The package prLogistic was built to assist the estimation of PR via logistic regression models adjusted by delta method and bootstrap for analysis of independent and correlated binary data. Two applications are presented to illustrate its use for analysis of independent observations and data from clustered studies.

MeSH terms

  • Cross-Sectional Studies
  • Logistic Models*
  • Odds Ratio
  • Prevalence