The Annals of Statistics
- Ann. Statist.
- Volume 34, Number 5 (2006), 2069-2097.
Conditional growth charts
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.
Ann. Statist. Volume 34, Number 5 (2006), 2069-2097.
First available in Project Euclid: 23 January 2007
Permanent link to this document
Digital Object Identifier
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Primary: 62F35: Robustness and adaptive procedures
Secondary: 62J20: Diagnostics 62P10: Applications to biology and medical sciences
Wei, Ying; He, Xuming. Conditional growth charts. Ann. Statist. 34 (2006), no. 5, 2069--2097. doi:10.1214/009053606000000623. https://projecteuclid.org/euclid.aos/1169571786.