Response‐Adaptive Regression for Longitudinal Data
Response‐Adaptive Regression for Longitudinal Data
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DOI：
10.1111/j.1541-0420.2010.01518.x
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发表时间：
2011-09
期刊：
影响因子：
1.9
通讯作者：
Shu-Chen Wu;H. Müller
中科院分区：
文献类型：
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作者：
Shu-Chen Wu;H. Müller
总结我们提出了一个函数线性回归的响应自适应模型，该模型适用于稀疏采样的纵向响应。我们的方法旨在预测响应轨迹，并通过直接调节预测器上响应的稀疏和不规则观测来建模回归关系，该预测器可以是标量，矢量或函数类型。这消除了对响应轨迹进行建模的需要，这对于稀疏的纵向数据来说是一项具有挑战性的任务，并且以前需要用于纵向数据的函数回归实现。所提出的方法被证明是上级相比，以前的功能回归方法的预测误差。它包含与生命科学中纵向数据的函数建模相关的各种回归设置。通过对猕猴桃体重增长的纵向研究以及对艾滋病临床试验中观察到的病毒载量和CD4细胞计数之间的动态关系的分析，说明了采用所提出的响应自适应方法对响应轨迹的改进预测。
Summary We propose a response‐adaptive model for functional linear regression, which is adapted to sparsely sampled longitudinal responses. Our method aims at predicting response trajectories and models the regression relationship by directly conditioning the sparse and irregular observations of the response on the predictor, which can be of scalar, vector, or functional type. This obliterates the need to model the response trajectories, a task that is challenging for sparse longitudinal data and was previously required for functional regression implementations for longitudinal data. The proposed approach turns out to be superior compared to previous functional regression approaches in terms of prediction error. It encompasses a variety of regression settings that are relevant for the functional modeling of longitudinal data in the life sciences. The improved prediction of response trajectories with the proposed response‐adaptive approach is illustrated for a longitudinal study of Kiwi weight growth and by an analysis of the dynamic relationship between viral load and CD4 cell counts observed in AIDS clinical trials.