Group variable selection in cardiopulmonary cerebral resuscitation data for veterinary patients

Young Joo Yoon; Cheolwoo Park; Erik Hofmeister; Sangwook Kang

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Group variable selection in cardiopulmonary cerebral resuscitation data for veterinary patients

机译：兽医患者心肺脑复苏数据中的组变量选择

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Cardiopulmonary cerebral resuscitation (CPCR) is a procedure to restore spontaneous circulation in patients with cardiopulmonary arrest (CPA). While animals with CPA generally have a lower success rate of CPCR than people do, CPCR studies in veterinary patients have been limited. In this paper, we construct a model for predicting success or failure of CPCR, and identifying and evaluating factors that affect the success of CPCR in veterinary patients. Due to reparametrization using multiple dummy variables or close proximity in nature, many variables in the data form groups, and thus a desirable method should take this grouping feature into account in variable selection. To accomplish these goals, we propose an adaptive group bridge method for a logistic regression model. The performance of the proposed method is evaluated under different simulated setups and compared with several other regression methods. Using the logistic group bridge model, we analyze data from a CPCR study for veterinary patients and discuss their implications on the practice of veterinary medicine.

机译：心肺脑复苏（CPCR）是一种恢复心肺骤停（CPA）患者自发性循环的程序。虽然具有CPA的动物通常比人具有较低的CPCR成功率，但对兽医患者的CPCR研究却受到限制。在本文中，我们构建了一个预测CPCR成功或失败以及确定和评估影响CPCR在兽医患者中成功的因素的模型。由于使用多个伪变量或本质上非常接近而进行了重新参数化，因此数据表中的许多变量形成了组，因此一种理想的方法应在变量选择中考虑此分组功能。为了实现这些目标，我们提出了一种用于逻辑回归模型的自适应群桥方法。在不同的模拟设置下评估了该方法的性能，并与其他几种回归方法进行了比较。使用逻辑组桥模型，我们分析了来自兽医患者的CPCR研究中的数据，并讨论了它们对兽医医学实践的影响。

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来源
《Journal of applied statistics》 |2012年第8期|p.1605-1621|共17页
作者
Young Joo Yoon; Cheolwoo Park; Erik Hofmeister; Sangwook Kang;
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作者单位

Department of Applied Statistics, Konkuk University, Seoul 143-701, Republic of Korea;

Department of Statistics, University of Georgia, Athens, GA 30602, USA;

Department of Small Animal Medicine and Surgery, University of Georgia, Athens, GA 30602, USA;

Department of Statistics, University of Connecticut, Storrs, CT 06269, USA;

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正文语种 eng
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关键词
bridge regression; cardiopulmonary cerebral resuscitation; group variable selection; logistic regression; veterinary patients;

机译：桥梁回归心肺脑复苏;组变量选择;逻辑回归兽医患者;

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7. Cardiopulmonary cerebral resuscitation using emergency cardiopulmonary bypass, coronary reperfusion therapy and mild hypothermia in patients with cardiac arrest outside the hospital [O] . Nagao Ken, Hayashi Nariyuki, Kanmatsuse Katsuo, 2000

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Group variable selection in cardiopulmonary cerebral resuscitation data for veterinary patients

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