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October 2006 Conditional growth charts
Ying Wei, Xuming He
Ann. Statist. 34(5): 2069-2097 (October 2006). DOI: 10.1214/009053606000000623

Abstract

Growth charts are often more informative when they are customized per subject, taking into account prior measurements and possibly other covariates of the subject. We study a global semiparametric quantile regression model that has the ability to estimate conditional quantiles without the usual distributional assumptions. The model can be estimated from longitudinal reference data with irregular measurement times and with some level of robustness against outliers, and it is also flexible for including covariate information. We propose a rank score test for large sample inference on covariates, and develop a new model assessment tool for longitudinal growth data. Our research indicates that the global model has the potential to be a very useful tool in conditional growth chart analysis.

Citation

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Ying Wei. Xuming He. "Conditional growth charts." Ann. Statist. 34 (5) 2069 - 2097, October 2006. https://doi.org/10.1214/009053606000000623

Information

Published: October 2006
First available in Project Euclid: 23 January 2007

zbMATH: 1106.62049
MathSciNet: MR2291494
Digital Object Identifier: 10.1214/009053606000000623

Subjects:
Primary: 62F35
Secondary: 62J20, 62P10

Rights: Copyright © 2006 Institute of Mathematical Statistics

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Vol.34 • No. 5 • October 2006
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