Quantile regression methods for reference growth charts
Quantile regression methods for reference growth charts
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DOI：
10.1002/sim.2271
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发表时间：
2006-04-30
影响因子：
2
通讯作者：
He, XM
中科院分区：
文献类型：
--
作者：
Wei, Y;Pere, A;He, XM
儿童身高和体重参考生长曲线的估计传统上依赖于基于参考人群样本的正态理论来构建分位数曲线族。特定年龄的参数变换已被用于显著拓宽这些常规理论方法的适用性。非参数分位数回归方法为估计条件分位数函数提供了一种补充策略。我们使用Cole和Green （Statistics it?）的惩罚似然方法比较估计的身高参考曲线。医学1992;11:1305-1319)，采用基于现代芬兰参考图表数据的分位数回归曲线。分位数回归方法的一个优点是，相对容易将先验增长和其他协变量纳入纵向增长数据的分析中。介绍了非等间距测量的分位数特定自回归模型，并说明了它们在诊断筛选中的应用。版权所有(c) 2005 John Wiley & Sons, Ltd。
Estimation of reference growth curves for children's height and weight has traditionally relied on normal theory to construct families of quantile curves based on samples from the reference population. Age-specific parametric transformation has been used to significantly broaden the applicability of these normal theory methods. Non-parametric quantile regression methods offer a complementary strategy for estimating conditional quantile functions. We compare estimated reference curves for height using the penalized likelihood approach of Cole and Green (Statistics it? Medicine 1992; 11:1305-1319) with quantile regression curves based on data used for modem Finnish reference charts. An advantage of the quantile regression approach is that it is relatively easy to incorporate prior growth and other covariates into the analysis of longitudinal growth data. Quantile specific auto regressive models for unequally spaced measurements are introduced and their application to diagnostic screening is illustrated. Copyright (c) 2005 John Wiley & Sons, Ltd.