Non‐parametric Bayesian multivariate metaregression: an application in environmental epidemiology
Non‐parametric Bayesian multivariate metaregression: an application in environmental epidemiology
复制标题
非参数贝叶斯多元元回归：在环境流行病学中的应用
DOI：
10.1111/rssc.12256
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Yeonseung Chung
中科院分区：
文献类型：
--
作者：
Gyuseok Sim;Ho Kim;A. Zanobetti;J. Schwartz;Yeonseung Chung
在生物医学研究中，Meta分析是一种流行的工具，可以将多项研究的联合收割机证据结合起来，以调查疗效-反应关联。两阶段分析方法用于Meta分析，其计算方便性和灵活性。第一阶段估计每项研究的相关性，而第二阶段结合研究特定估计值，纠正研究特定误差。第二阶段通常包含研究特定的协变量（元预测因子），称为元回归。两阶段Meta分析的一个有用应用是环境暴露对健康影响的流行病学研究，该研究通常分析从多个地点收集的暴露和健康结果的时间序列数据。第一阶段对位置特定的关联进行建模，这通常由多个参数表示，因为关联是非线性或延迟的，第二阶段进行多变量元回归，将位置特定的特征作为元预测器。目前使用的多元元回归是正态线性回归的一种形式，它可能受到限制，因为它假设元预测器的线性，残差正态性和方差齐性。在本文中，我们提出了一个灵活的多元元回归的非参数贝叶斯建模框架，并结合残差空间依赖。建议的元回归进行了评估，通过模拟研究，并应用于调查温度与死亡率的关联，在135个美国城市。
In biomedical research, meta‐analysis is a popular tool to combine evidence from multiple studies to investigate an exposure–response association. A two‐stage analytical approach is used in meta‐analysis for its computational convenience and flexibility. The first stage estimates the association for each study whereas the second stage combines the study‐specific estimates correcting for the study‐specific error. The second stage often incorporates study‐specific covariates (metapredictors) and is called metaregression. One application where the two‐stage meta‐analysis is useful is an epidemiological study for the health effects of environmental exposure, which often analyses time series data of exposure and health outcome collected from multiple locations. The first stage models location‐specific association, which is often represented by multiple parameters as the association is non‐linear or delayed, and the second stage conducts a multivariate metaregression with location‐specific characteristics as metapredictors. The currently used multivariate metaregression is a form of normal linear regression, which may be limited as it assumes linearity in metapredictors, residual normality and homoscedasticity. In the paper, we propose a flexible multivariate metaregression in a non‐parametric Bayesian modelling framework incorporating a residual spatial dependence. The proposed metaregression was evaluated through a simulation study and applied to investigate a temperature–mortality association in the 135 US cities.
影响因子：
4.4
作者：
Rodríguez A;Dunson DB
通讯作者：
Dunson DB
影响因子：
4.4
作者：
Müller P;Mitra R
通讯作者：
Mitra R