uni_reg: Univariate regression (Odds, Risk, or Rate Ratios)

In gtregression: Tools for Creating Publication-Ready Regression Tables

Univariate regression (Odds, Risk, or Rate Ratios)

Description

Performs univariate regression for each exposure on a binary, continuous, or count outcome. Depending on 'approach', returns either Odds Ratios (OR), Risk Ratios (RR), or Incidence Rate Ratios (IRR).

Usage

uni_reg(data, outcome, exposures, approach = "logit")

Arguments

data	A data frame containing the variables.
outcome	outcome variable (binary, continuous, or count).
exposures	A vector of predictor variables.
approach	Modeling approach to use. One of: '"logit"' (OR), '"log-binomial"' (RR), '"poisson"' (IRR), '"robpoisson"' (RR), '"linear"' (Beta coefficients), '"negbin"' (IRR)

Details

This function requires the following packages: 'dplyr', 'purrr', 'gtsummary', 'risks'.

Value

A list of class 'uni_reg' and 'gtsummary::tbl_stack', including:

• A publication-ready regression table ('tbl_stack')

• Accessor elements:

  • '$models': Fitted regression models for each exposure

  • '$model_summaries': Tidy model summaries

  • '$reg_check': Diagnostics (only for linear regression)

See Also

multi_reg, plot_reg

Examples

data(PimaIndiansDiabetes2, package = "mlbench")
library(dplyr)
pima <- PimaIndiansDiabetes2 |>
  dplyr::mutate(diabetes = ifelse(diabetes == "pos", 1, 0))
uni_reg(pima, outcome = "diabetes", exposures = "age", approach = "logit")

gtregression documentation built on Aug. 18, 2025, 5:23 p.m.