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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Vydáno v:	Journal of the Korean Statistical Society Ročník 52; číslo 1; s. 1 - 32
Hlavní autoři:	Ma, Wei, Zhang, Ting, Wang, Lei
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Singapore Springer Nature Singapore 01.03.2023 Springer Nature B.V
Témata:	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
On-line přístup:	Získat plný text
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