Main content


Date created: | Last Updated:


Creating DOI. Please wait...

Create DOI

Category: Project

Description: Petscher and Logan (2014)’s description of quantile regression might mislead readers to believe it would estimate the relation between an outcome, y, and one or more predictors, x, at different quantiles of the unconditional distribution of y. However, quantile regression models the conditional quantile function of y given x just as linear regression models the conditional mean function. This article’s contribution is twofold: First, it discusses potential consequences of methodological misconceptions and formulations of Petscher and Logan (2014)’s presentation by contrasting features of quantile regression and linear regression. Secondly, it reinforces the importance of correct understanding of quantile regression in empirical research by illustrating similarities and differences of various quantile regression estimators and linear regression using simulated data.

License: BSD 2-Clause "Simplified" License

Has supplemental materials for What Quantile Regression Does and Doesn't Do on SocArXiv


Add important information, links, or images here to describe your project.


Loading files...




Recent Activity

Loading logs...

OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.
This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.