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Prevalence ratio estimation via logistic regression: a tool in R.

Leila Denise Alves Ferreira AmorimRaydonal Ospina
Published in: Anais da Academia Brasileira de Ciencias (2021)
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.
Keyphrases
  • cross sectional
  • risk factors
  • electronic health record
  • big data
  • case control
  • type diabetes
  • metabolic syndrome
  • skeletal muscle
  • insulin resistance