Group variable selection in cardiopulmonary cerebral resuscitation data for veterinary patients

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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.
Publisher
TAYLOR & FRANCIS LTD
Issue Date
2012
Language
English
Article Type
Article
Citation

JOURNAL OF APPLIED STATISTICS, v.39, no.7, pp.1605 - 1621

ISSN
0266-4763
DOI
10.1080/02664763.2012.661929
URI
http://hdl.handle.net/10203/285779
Appears in Collection
MA-Journal Papers(저널논문)
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