Improved multiple quantile regression estimation with nonignorable dropouts

This paper proposes an efficient approach to deal with the issue of estimating multiple quantile regression (MQR) model. The relationship between the multiple quantiles and within-subject correlation is accommodated to improve efficiency in the presence of nonignorable dropouts. We adopt empirical l...

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Bibliographic Details

Published in:	Journal of the Korean Statistical Society Vol. 52; no. 1; pp. 1 - 32
Main Authors:	Ma, Wei, Zhang, Ting, Wang, Lei
Format:	Journal Article
Language:	English
Published:	Singapore Springer Nature Singapore 01.03.2023 Springer Nature B.V
Subjects:	Applied Statistics Bayesian Inference Mathematics and Statistics Research Article Statistical Theory and Methods Statistics Statistics and Computing/Statistics Programs Within-subject correction Quadratic inference function Nonignorable dropout Smoothed empirical likelihood
ISSN:	1226-3192, 2005-2863
Online Access:	Get full text
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