Modeling sign concordance of quantile regression residuals with multiple outcomes
Columbu Silvia
;Frumento Paolo;Bottai Matteo
2023-01-01
Abstract
Quantile regression permits describing how quantiles of a scalar response vari- able depend on a set of predictors. Because a unique de nition of multivariate quantiles is lacking, extending quantile regression to multivariate responses is somewhat complicated. In this paper, we describe a simple approach based on a two-step procedure: in the rst step, quantile regression is applied to each re- sponse separately; in the second step, the joint distribution of the signs of the residuals is modeled through multinomial regression. The described approach does not require a multidimensional de nition of quantiles, and can be used to capture important features of a multivariate response and assess the e ects of co- variates on the correlation structure. We apply the proposed method to analyze two di erent datasets.File | Size | Format | |
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Columbu_IJB2022.pdf Open Access from 01/08/2023
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