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.