Asymptotic confidence regions for kernel smoothing of a varying-coefficient model with longitudinal data
Asymptotic confidence regions for kernel smoothing of a varying-coefficient model with longitudinal data
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DOI：
10.2307/2670054
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发表时间：
1998-12-01
影响因子：
3.7
通讯作者：
Hoover, DR
中科院分区：
文献类型：
--
作者：
Wu, CO;Chiang, CT;Hoover, DR
本文考虑了基于纵向观测值（Y-ij，X-i（t（ij）），t（ij）），i = 1，.的变系数模型Y（t）= X-T（t）beta（t）+ β（t）的k + 1维非参数分量beta（t）的估计，n，j = i，...，n（i），其中t（ij）是第i个受试者的第j个观察设计时间点t，Y-ij和X-i（t（ij））是第i个受试者在t（ij）时的实值结果和Rk+1值协变量向量。受试者是独立选择的，但受试者内的重复测量可能相关。渐近分布被建立用于最小化局部最小二乘准则的beta（t）的核估计。这些渐近分布被用来构造一类近似的逐点和同时的置信区域的beta（t）。应用这些方法的流行病学研究，我们表明，我们的程序是有用的预测HIV（人类免疫缺陷病毒）感染者之间的CD 4（辅助性T淋巴细胞）细胞的变化。我们的程序的有限样本性质进行了研究，通过Monte Carlo模拟。
We consider the estimation of the k + 1-dimensional nonparametric component beta(t) of the varying-coefficient model Y(t) = X-T(t)beta(t) + epsilon(t) based on longitudinal observations (Y-ij, X-i(t(ij)), t(ij)), i = 1,..., n,j = i,..., n(i), where t(ij) is the jth observed design time point t of the ith subject and Y-ij and X-i(t(ij)) are the real-valued outcome and Rk+1 valued covariate vectors of the ith subject at t(ij). The subjects are independently selected, but the repeated measurements within subject are possibly correlated. Asymptotic distributions are established for a kernel estimate of beta(t) that minimizes a local least squares criterion. These asymptotic distributions are used to construct a class of approximate pointwise and simultaneous confidence regions for beta(t). Applying these methods to an epidemiological study, we show that our procedures are useful for predicting CD4 (T-helper lymphocytes) cell changes among HIV (human immunodeficiency virus)-infected persons. The finite-sample properties of our procedures are studied through Monte Carlo simulations.