Comparison of meta-analysis versus analysis of variance of individual patient data
Comparison of meta-analysis versus analysis of variance of individual patient data
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DOI：
10.2307/2534018
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发表时间：
1998-03-01
期刊：
影响因子：
1.9
通讯作者：
Sampson, A
中科院分区：
文献类型：
--
作者：
Olkin, I;Sampson, A
荟萃分析是一种综合独立研究结果的方法。我们考虑的情况下，有多个治疗和控制，与估计的相对效果的基础上连续的结果，每种治疗的目标。即使所有数据都可用，而不仅仅是汇总数据，使用治疗对比的荟萃分析估计值也变得很常见。或者，我们可以使用无交互作用的双向方差分析模型，其中一个因素是研究，一个因素是治疗。对于不平衡的情况下，我们得到了令人惊讶的结果，治疗对比的标准荟萃分析估计是相同的线性模型中的治疗对比的最小二乘估计。由于个体患者数据的荟萃分析在数据检索方面可能比汇总数据的荟萃分析成本高得多，因此这种等效性提供了具有成本效益的分析。
Meta-analysis is a method of synthesizing the results of independent studies. We consider the case in which there are multiple treatments and a control, with the goal of estimating the relative effect of each treatment based on continuous outcomes. Even when all data are available, rather than only summary data, it has become common to use meta-analytic estimators of treatment contrasts. Alternatively, we could use a two-way analysis of variance model with no interaction in which one factor is study and one factor is treatment. For the unbalanced case, we obtain the surprising result that the standard meta-analysis estimates of treatment contrasts are identical to the least squares estimators of treatment contrasts in the linear model. Because a meta-analysis of individual patient data can be considerably more costly in terms of data retrieval than a meta-analysis of summary data, this equivalence provides for cost-efficient analysis.