gtregression - Tools for Creating Publication-Ready Regression Tables
Simplifies regression modelling in R by integrating
modelling, diagnostics, visualisation, and summarisation tools
into a cohesive, user-friendly interface. Designed to be
accessible for researchers, particularly those in Low- and
Middle-Income Countries (LMIC). Supports logistic, linear,
count, matched case-control, ordinal, multinomial, multilevel,
Cox, parametric survival, and competing-risk regression. Built
upon widely accepted statistical methods, including logistic
regression (Hosmer et al. 2013, ISBN:9781118548429),
log-binomial regression (Spiegelman and Hertzmark 2005
<doi:10.1093/aje/kwi188>), Firth penalized logistic regression
(Firth 1993 <doi:10.1093/biomet/80.1.27>), Poisson and robust
Poisson regression (Zou 2004 <doi:10.1093/aje/kwh090>),
negative binomial regression (Hilbe 2011, ISBN:9780521179515),
Cox proportional hazards regression, parametric survival
regression, causal mediation analysis, and linear regression
(Kutner et al. 2005, ISBN:9780071122214). Leverages multiple
dependencies to ensure high-quality output and generate
reproducible, publication-ready tables in alignment with best
practices in epidemiology and applied statistics.
