Hypothesis testing in semiparametric additive mixed models
Hypothesis testing in semiparametric additive mixed models
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DOI：
10.1093/biostatistics/4.1.57
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发表时间：
2003-01-01
期刊：
影响因子：
2.1
通讯作者：
Lin, XH
中科院分区：
文献类型：
--
作者：
Zhang, DW;Lin, XH
我们考虑检验半参数可加混合模型中的非参数函数是否是简单的定次多项式，例如简单的线性函数。该检验为检验参数模型和非参数模型提供了一种拟合优度检验。它基于非参数函数的光滑样条估计量的混合模型表示和方差分量得分检验，将平滑参数的逆视为额外的方差分量。我们还考虑检验两组的半参数加性混合模型中两个非参数函数的等价性，例如治疗组和安慰剂组。建议的测试应用于流行病学研究和临床试验的数据，并通过模拟对其性能进行评估。
We consider testing whether the nonparametric function in a semiparametric additive mixed model is a simple fixed degree polynomial, for example, a simple linear function. This test provides a goodness-of-fit test for checking parametric models against nonparametric models. It is based on the mixed-model representation of the smoothing spline estimator of the nonparametric function and the variance component score test by treating the inverse of the smoothing parameter as an extra variance component. We also consider testing the equivalence of two nonparametric functions in semiparametric additive mixed models for two groups, such as treatment and placebo groups. The proposed tests are applied to data from an epidemiological study and a clinical trial and their performance is evaluated through simulations.