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What Quantile Regression Does and Doesn't Do: A Commentary on Petscher and Logan (2014)
[journal article]
Abstract Petscher and Logan's (2014) description of quantile regression (QR) 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, QR models the conditional quantile functio... view more
Petscher and Logan's (2014) description of quantile regression (QR) 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, QR 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's (2014) presentation by contrasting features of QR and linear regression. Second, it reinforces the importance of correct understanding of QR in empirical research by illustrating similarities and differences in various QR estimators and linear regression using simulated data.... view less
Keywords
regression; estimation; linear model; simulation
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Document language
English
Publication Year
2019
Page/Pages
p. 1442-1452
Journal
Child development, 90 (2019) 4
DOI
https://doi.org/10.1111/cdev.13141
ISSN
1467-8624
Status
Postprint; peer reviewed
Licence
Deposit Licence - No Redistribution, No Modifications