Integration of aggregated data in causally interpretable meta-analysis by inverse weighting
通过逆向加权将汇总数据纳入可作因果解释的元分析
Obtaining causally interpretable meta-analysis results is challenging when there are differences in the distribution of effect modifiers between eligible trials. To overcome this, recent work on transportability methods has considered standardizing results of individual studies over the case-mix of a target population, prior to pooling them as in a classical random-effect meta-analysis. One practical challenge, however, is that case-mix standardization often requires…