Borrowing of strength and study weights in multivariate and network meta-analysis.
Borrowing of strength and study weights in multivariate and network meta-analysis.
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DOI：
10.1177/0962280215611702
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发表时间：
2017-12
影响因子：
2.3
通讯作者：
Riley RD
中科院分区：
文献类型：
--
作者：
Jackson D;White IR;Price M;Copas J;Riley RD
多变量和网络荟萃分析有可能使一个效应的估计均值从其他感兴趣效应的数据中借用力量。这种借用力量的程度通常是非正式评估的。我们提出了新的数学定义的“借势”。我们的主要建议是基于分数统计量的分解，我们可以解释为比较多变量和单变量模型的估计精度。因此，我们对借势的定义仿效了通常的非正式评估。我们还推导出一种计算研究权重的方法，我们将其嵌入到与我们借用强度统计相同的框架中，以便百分比研究权重可以与多变量和网络荟萃分析的结果一起使用，就像在传统的单变量荟萃分析中一样。我们的建议说明使用三个荟萃分析，涉及多个结果的相关影响，多个危险因素的关联和多种治疗（网络荟萃分析）。
Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of ‘borrowing of strength’. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis).