Abstract
Linear regression is a key statistical method for exploring relationships between a continuous outcome and predictors. Ensuring its assumptions are met is vital for accurate estimates and valid p-values. However, misconceptions about these assumptions, especially among non-statisticians, still exist and often hinder proper diagnostics. To address this challenge, we developed ReDiag, an interactive Shiny web application designed to assist researchers in assessing the normality, homoscedasticity, and linearity assumptions and handle violations effectively. ReDiag’s source code and an extensive tutorial applied to two example published datasets are available on GitHub. The app can be accessed via shinyapps.io.