SEMIPARAMETRIC MODELS FOR LONGITUDINAL DATA WITH APPLICATION TO CD4 CELL NUMBERS IN HIV SEROCONVERTERS
SEMIPARAMETRIC MODELS FOR LONGITUDINAL DATA WITH APPLICATION TO CD4 CELL NUMBERS IN HIV SEROCONVERTERS
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DOI：
10.2307/2532783
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发表时间：
1994-09-01
期刊：
影响因子：
1.9
通讯作者：
DIGGLE, PJ
中科院分区：
文献类型：
--
作者：
ZEGER, SL;DIGGLE, PJ
本文介绍了一种半参数模型的纵向数据，说明其应用程序的数据的时间演变的CD4细胞数量在HIV血清转换。该模型的基本成分是协变量调整的参数线性模型，平滑时间趋势的非参数估计，单个受试者测量值之间的序列相关性，以及随机测量误差。后拟合算法与交叉验证处方结合使用以拟合模型。该应用程序的一个显着特点是，艾滋病毒感染的发作与CD4细胞的突然下降有关，随后是较长时间的缓慢衰减。该模型还用于通过将个人数据与人口曲线相结合来估计个人曲线。向总体平均轨迹的收缩以自然的方式由数据的估计协方差结构控制。
The paper describes a semiparametric model for longitudinal data which is illustrated by its application to data on the time evolution of CD4 cell numbers in HIV seroconverters. The essential ingredients of the model are a parametric linear model for covariate adjustment, a nonparametric estimation of a smooth time trend, serial correlation between measurements on an individual subject, and random measurement error. A back-fitting algorithm is used in conjunction with a cross-validation prescription to fit the model. A notable feature in the application is that the onset of HIV infection is associated with a sudden drop in CD4 cells followed by a longer-term slower decay. The model is also used to estimate an individual's curve by combining his data with the population curve. Shrinkage toward the population mean trajectory is controlled in a natural way by the estimated covariance structure of the data.