Diamond Plots: a tutorial to introduce a visualisation tool that facilitates interpretation and comparison of multiple sample estimates while respecting their inaccuracy

Abstract

Although a shift from a focus on null hypothesis significance testing to reporting effect sizes and confidence intervals has been advocated for decades, researchers have been slow to implement this shift. One of the reasons may be that working with confidence intervals is interpreted as inconvenient. Diamond plots are a visualisation technique to ameliorate this disadvantage. The current paper introduces an implementation of diamond plots in the free and open source software R. This implementation is flexible and designed to also be accessible to researchers that are not used to working with R. The current paper also includes a tutorial to enable researchers to start producing diamond plots themselves with minimal effort. Combining a shift from reporting point estimates and confidence intervals in tables to using diamond plots with full disclosure enables presenting reports in a readable manner without loss of detail.