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幼儿急性中耳感染:基于多时间尺度的贝叶斯分析

Acute middle ear infection in small children: a Bayesian analysis using multiple time scales.

作者信息

Andreev A, Arjas E

机构信息

Department of Mathematical Sciences, University of Oulu, Finland.

出版信息

Lifetime Data Anal. 1998;4(2):121-37. doi: 10.1023/a:1009629422623.

Abstract

The study is based on a sample of 965 children living in Oulu region (Finland), who were monitored for acute middle ear infections from birth to the age of two years. We introduce a nonparametrically defined intensity model for ear infections, which involves both fixed and time dependent covariates, such as calendar time, current age, length of breast-feeding time until present, or current type of day care. Unmeasured heterogeneity, which manifests itself in frequent infections in some children and rare in others and which cannot be explained in terms of the known covariates, is modelled by using individual frailty parameters. A Bayesian approach is proposed to solve the inferential problem. The numerical work is carried out by Monte Carlo integration (Metropolis-Hastings algorithm).

摘要

该研究基于对居住在奥卢地区(芬兰)的965名儿童的抽样调查,这些儿童从出生到两岁期间接受了急性中耳感染监测。我们引入了一个非参数定义的耳部感染强度模型,该模型涉及固定和随时间变化的协变量,如日历时间、当前年龄、到目前为止的母乳喂养时间长度或当前的日托类型。未测量的异质性表现为一些儿童感染频繁而另一些儿童感染罕见,且无法用已知协变量解释,通过使用个体脆弱性参数对其进行建模。提出了一种贝叶斯方法来解决推断问题。数值工作通过蒙特卡罗积分(梅特罗波利斯-黑斯廷斯算法)进行。

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