Measures of effect for cross-sectional studies

Abstract

Carta aos editoresfor the analysis of binary outcomes in cross-sectional studies using the PR rather than OR. The simplest way is to transform the ORs obtained by logistic regression into PRs. 3,4 Another possibility is to use a statistical model that directly estimates the PR and its confidence interval. Alternatives explored in the epidemiological literature are Cox regression with equal times of follow-up assigned to all individuals, log-binomial regression (a generalized linear model with a logarithmic link function and binomial distribution for the residue), Poisson regression with robust variance and complementary log-log model, where the link function is log (-log 3,5 Although the use of OR for cross sectional studies is not necessarily wrong, authors and referees should be aware of its correct interpretation and alternatives to it for cross sectional studies.