ANALYSIS OF HEAD INJURIES USING A BAYESIAN VECTOR GENERALIZED ADDITIVE MODEL

Paul J. Hewson

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ANALYSIS OF HEAD INJURIES USING A BAYESIAN VECTOR GENERALIZED ADDITIVE MODEL

机译：贝叶斯矢量广义相加模型在颅脑损伤分析中的应用

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The potential of cycle helmets to reduce head injury remains controversial. Although several case-control studies have been published, ecological analyses of head injury remain commonplace, presumably because of the availability of data and policy-makers' preference for 'whole population' studies. Given that such population-level analysis will be conducted, this paper models the odds ratio between different road-user groups over time. We use a Bayesian implementation of a vector generalized additive model in order to examine the odds ratio for head injury when comparing male cyclists with female cyclists, male pedestrians with male cyclists, and female pedestrians with female cyclists over a period when helmet-wearing rates were thought to diverge by gender.

机译：自行车头盔减轻头部伤害的潜力仍然存在争议。尽管已经发表了一些病例对照研究，但是头部损伤的生态学分析仍然很普遍，这可能是由于数据的可获得性以及政策制定者对“全民”研究的偏爱。考虑到将进行这种人口水平的分析，本文对不同道路使用者群体之间随时间变化的优势比进行建模。我们使用矢量广义加性模型的贝叶斯实现，以便在比较头盔佩戴率达到一定时期的男性骑自行车的人与女性骑自行车的人，男性自行车的行人与女性自行车的行人时，检查头部受伤的几率。被认为因性别而异。

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来源
《Australian & New Zealand journal of statistics》 |2011年第2期|p.233-246|共14页
作者
Paul J. Hewson;
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作者单位

School of Computing and Mathematics, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK;

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正文语种 eng
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关键词
cycle helmets; generalized additive mixed models; markov Chain monte carlo; penalized splines.;

机译：自行车头盔;广义加性混合模型;马尔可夫链蒙特卡洛;点状花键。;

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ANALYSIS OF HEAD INJURIES USING A BAYESIAN VECTOR GENERALIZED ADDITIVE MODEL

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