Olkin I, Sampson A
Department of Statistics, Stanford University, California 94305, USA.
Biometrics. 1998 Mar;54(1):317-22.
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.
荟萃分析是一种综合独立研究结果的方法。我们考虑存在多种治疗方法和一个对照的情况，目标是基于连续结果估计每种治疗方法的相对效果。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量也已变得很常见。或者，我们可以使用一个无交互作用的双向方差分析模型，其中一个因素是研究，另一个因素是治疗。对于不平衡的情况，我们得到了一个令人惊讶的结果，即治疗对比的标准荟萃分析估计量与线性模型中治疗对比的最小二乘估计量相同。由于就数据检索而言，个体患者数据的荟萃分析可能比汇总数据的荟萃分析成本高得多，这种等效性提供了具有成本效益的分析方法。
