Doubly structured sparsity for grouped multivariate responses with application to functional outcome score modeling.
Doubly structured sparsity for grouped multivariate responses with application to functional outcome score modeling.
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DOI：
10.1002/sim.9740
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发表时间：
2023-07-10
影响因子：
2
通讯作者：
Leonard, Julie C.
中科院分区：
文献类型：
--
作者：
Huling, Jared D.;Lundine, Jennifer P.;Leonard, Julie C.
这项工作的动机是需要准确地建模与儿科功能状态相关的反应向量，使用住院康复访问的行政健康数据。答复的组成部分具有已知的和结构化的相互关系。为了在建模中利用这些关系，我们开发了一种双管齐下的正则化方法来跨响应借用信息。我们方法的第一个组成部分鼓励在可能重叠的相关答复组中联合选择每个变量的影响，第二个组成部分鼓励相互缩小对相关答复的影响。由于我们的激励研究中的反应不是正态分布的，所以我们的方法不依赖于反应的多元正态假设。我们证明，在我们的惩罚的自适应版本下，我们的方法得到相同的估计的渐近分布，就好像我们事先知道哪些变量具有非零影响，哪些变量在某些结果中具有相同的影响。我们展示了我们的方法在广泛的数值研究中的表现，以及在一家大型儿童医院使用管理健康数据对患有神经损伤或疾病的儿童人群进行儿科患者功能状态预测的应用。
This work is motivated by the need to accurately model a vector of responses related to pediatric functional status using administrative health data from inpatient rehabilitation visits. The components of the responses have known and structured interrelationships. To make use of these relationships in modeling, we develop a two-pronged regularization approach to borrow information across the responses. The first component of our approach encourages joint selection of the effects of each variable across possibly overlapping groups of related responses and the second component encourages shrinkage of effects towards each other for related responses. As the responses in our motivating study are not normally-distributed, our approach does not rely on an assumption of multivariate normality of the responses. We show that with an adaptive version of our penalty, our approach results in the same asymptotic distribution of estimates as if we had known in advance which variables have non-zero effects and which variables have the same effects across some outcomes. We demonstrate the performance of our method in extensive numerical studies and in an application in the prediction of functional status of pediatric patients using administrative health data in a population of children with neurological injury or illness at a large children’s hospital.
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DOI：
10.1198/jcgs.2010.09188
发表时间：
2010
期刊：
Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America
影响因子：
--
作者：
Rothman AJ;Levina E;Zhu J
通讯作者：
Zhu J
影响因子：
4.5
作者：
Zhang, Cun-Hui
通讯作者：
Zhang, Cun-Hui
影响因子：
1.9
作者：
Huling JD;Yu M;Liang M;Smith M
通讯作者：
Smith M
ADMM对于多块凸最小化问题的直接扩展并不一定收敛
影响因子：
2.7
作者：
Chen, Caihua;He, Bingsheng;Yuan, Xiaoming
通讯作者：
Yuan, Xiaoming
影响因子：
8
作者：
Schneier, Andrew J.;Shields, Brenda J.;Smith, Gary A.
通讯作者：
Smith, Gary A.