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A NEW MULTILEVEL MODELING APPROACH FOR CLUSTERED SURVIVAL DATA
Econometric Theory ( IF 1.0 ) Pub Date : 2020-03-03 , DOI: 10.1017/s0266466619000343
Jinfeng Xu , Mu Yue , Wenyang Zhang

In multilevel modeling of clustered survival data, to account for the differences among different clusters, a commonly used approach is to introduce cluster effects, either random or fixed, into the model. Modeling with random effects may lead to difficulties in the implementation of the estimation procedure for the unknown parameters of interest because the numerical computation of multiple integrals may become unavoidable when the cluster effects are not scalars. On the other hand, if fixed effects are used, there is a danger of having estimators with large variances because there are too many nuisance parameters involved in the model. In this article, using the idea of the homogeneity pursuit, we propose a new multilevel modeling approach for clustered survival data. The proposed modeling approach does not have the potential computational problem as modeling with random effects, and it also involves far fewer unknown parameters than modeling with fixed effects. We also establish asymptotic properties to show the advantages of the proposed model and conduct intensive simulation studies to demonstrate the performance of the proposed method. Finally, the proposed method is applied to analyze a dataset on the second-birth interval in Bangladesh. The most interesting finding is the impact of some important factors on the length of the second-birth interval variation over clusters and its homogeneous structure.

中文翻译:

一种用于聚类生存数据的新的多层次建模方法

在聚类生存数据的多级建模中,为了解释不同聚类之间的差异,一种常用的方法是在模型中引入随机或固定的聚类效应。具有随机效应的建模可能会导致对感兴趣的未知参数的估计过程的实施困难,因为当集群效应不是标量时,多重积分的数值计算可能变得不可避免。另一方面,如果使用固定效应,则存在具有较大方差的估计量的危险,因为模型中涉及太多令人讨厌的参数。在本文中,我们利用同质性追求的思想,提出了一种新的聚类生存数据多层次建模方法。所提出的建模方法不存在像随机效应建模那样潜在的计算问题,而且它所涉及的未知参数也比使用固定效应建模要少得多。我们还建立了渐近属性来展示所提出模型的优势,并进行深入的模拟研究来证明所提出方法的性能。最后,将所提出的方法应用于分析孟加拉国二胎间隔的数据集。最有趣的发现是一些重要因素对星团的二胎间隔变化长度及其同质结构的影响。我们还建立了渐近属性来展示所提出模型的优势,并进行深入的模拟研究来证明所提出方法的性能。最后,将所提出的方法应用于分析孟加拉国二胎间隔的数据集。最有趣的发现是一些重要因素对星团的二胎间隔变化长度及其同质结构的影响。我们还建立了渐近属性来展示所提出模型的优势,并进行深入的模拟研究来证明所提出方法的性能。最后,将所提出的方法应用于分析孟加拉国二胎间隔的数据集。最有趣的发现是一些重要因素对星团的二胎间隔变化长度及其同质结构的影响。
更新日期:2020-03-03
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