Unravelling the Nuances of Data With Quantile Regression: A Comprehensive Tutorial

ABSTRACT In applied psychology, traditional statistical methods often provide only a broad overview, potentially overlooking nuanced variable relationships. This article presents a comprehensive tutorial on quantile regression (QR), a statistical modelling technique ideally suited for psychological data analysis. Unlike conventional regression, QR examines relationships across different quantiles of the data distribution, revealing complex dynamics and offering robustness to non‐normality and heteroscedasticity. We demonstrate its utility through a practical example, analysing the relationship between age and life satisfaction, supported by annotated R code. The tutorial emphasises grounding QR in a sound theoretical framework and introduces the quantile loss approach as an alternative to p value interpretation. By providing both theoretical understanding and practical tools, this tutorial aims to empower researchers to improve the depth and reproducibility of their findings in psychological research.