Unraveling the Nuances of Data with Quantile Regression: A Comprehensive Tutorial

Resumen

Update: This preprint has been accepted for publication in the International Journal of Psychology and has undergone significant revisions. The final, peer-reviewed version will be available in a forthcoming special issue, the publication date of which has not yet been determined. In applied psychology, traditional statistical methods often provide only a broad overview, missing the intricate variable relationships. This article introduces a comprehensive tutorial on quantile regression, a nuanced statistical modeling technique ideal for psychological data analysis. Diverging from conventional regression, quantile regression delves into diverse relationships across data quantiles, uncovering complex dynamics. We demonstrate its utility in various applied psychology sub-disciplines, supported by practical, annotated R code examples. This tutorial aims to democratize this advanced statistical tool, empowering researchers to probe deeper into their data's subtleties and enrich psychological research.

Áreas y palabras clave

Cómo citar (APA 7)

Mabire-Yon, R. (2024). Unraveling the Nuances of Data with Quantile Regression: A Comprehensive Tutorial. https://doi.org/10.31234/osf.io/4xkuc