Model checking for partially linear models with missing responses at random

Model checking for partially linear models with missing responses at random
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对随机缺失响应的部分线性模型进行模型检查

DOI:
10.1016/j.jmva.2008.07.002
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发表时间:
2009-04
影响因子:
1.6
通讯作者:
Sun Zhihua, 王启华, Dai Pengjie
Sun Zhihua, 王启华, Dai Pengjie
中科院分区:
数学2区
文献类型:
--
作者:
Sun Zhihua, 王启华, Dai Pengjie

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本文研究了部分线性模型在部分响应随机缺失时的模型检验问题。通过插补和边际逆概率加权的方法,构造了两个完整的数据集。基于两个完整的数据集,我们建立了两个经验的过程为基础的测试,以检查模型的部分线性的充分性。在原假设和局部备择假设下分别得到了检验统计量的渐近分布。应用重抽样方法来获得检验统计量的零分布的近似。仿真结果表明,所提出的测试工作以及所提出的方法有更好的有限样本性能相比,完整的情况下(CC)分析,丢弃所有的主题与缺失数据。
In this paper, we investigate the model checking problem for a partial linear model while some responses are missing at random. By imputation and marginal inverse probability weighted methods, two completed data sets are constructed. Based on the two completed data sets, we build two empirical process-based tests for examining the adequacy of partial linearity of the model. The asymptotic distributions of the test statistics under the null hypothesis and local alternative hypotheses are obtained respectively. A re-sampling approach is applied to obtain the approximation to the null distributions of the test statistics. Simulation results show that the proposed tests work well and both proposed methods have better finite sample properties compared with the complete case (CC) analysis which discards all the subjects with missing data.
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发表时间: 2007-03
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