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prLogistic  

Estimation of Prevalence Ratios via Logistic Regression Models
View on CRAN: Click here


Download and install prLogistic package within the R console
Install from CRAN:
install.packages("prLogistic")

Install from Github:
library("remotes")
install_github("cran/prLogistic")

Install by package version:
library("remotes")
install_version("prLogistic", "2.0.2")



Attach the package and use:
library("prLogistic")
Maintained by
Raydonal Ospina
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-09-19
Latest Update: 2026-06-19
Description:
Estimates adjusted prevalence ratios (PR) and their confidence intervals from logistic regression models, addressing the well-known limitation of odds ratios (OR) as approximations to PR in cross-sectional studies with common outcomes. Supports independent observations (glm()), clustered/multilevel data (glmer() from 'lme4'), longitudinal data via Generalised Estimating Equations (geeglm() from 'geepack'), and complex survey designs (svyglm() from 'survey'). Inference is available via the delta method (conditional and marginal standardisation) and via bootstrap (normal-approximation and percentile intervals). Continuous covariates are handled through user-specified or median-based reference values; flexible baseline specification allows any reference category to be chosen for factor predictors. Based on the methodology described in Amorim & Ospina (2021) <doi:10.1590/0001-3765202120190316>.
How to cite:
Raydonal Ospina (2013). prLogistic: Estimation of Prevalence Ratios via Logistic Regression Models. R package version 2.0.2, https://cran.r-project.org/web/packages/prLogistic. Accessed 14 Jul. 2026.
Previous versions and publish date:
(2026-07-09 06:43), 1.0 (2011-07-23 16:41), 1.1 (2011-10-26 20:00), 1.2 (2013-09-19 18:47)
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Complete documentation for prLogistic
Functions, R codes and Examples using the prLogistic R package
Full prLogistic package functions and examples
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