Original
Designing multi‐site studies for external validity: Site selection via synthetic purposive sampling
Abstract
Abstract Multi‐site/context studies have become popular strategies to address the most common and challenging external validity concerns about contexts. Under such studies, scholars conduct causal studies in each site and evaluate whether findings generalize across sites. Despite the potential, there has been little guidance on the fundamental research design question—how should we select sites for external validity? Existing approaches have challenges: random sampling of sites is often infeasible, while the current practice of purposive sampling is suboptimal without statistical guarantees. We propose synthetic purposive sampling (SPS), which optimally selects diverse sites for external validity. SPS combines ideas of purposive sampling and the synthetic control method—it selects diverse sites such that nonselected sites are well approximated by the weighted average of the selected sites. We illustrate its general applicability using both experimental and observational studies. Overall, this paper offers a new statistical foundation to design multisite studies for external validity.
中文
设计面向外部效度的多地点研究：通过合成目的性抽样进行地点选择
摘要
多地点/情境研究已成为应对关于情境的最常见且最具挑战性的外部效度关切的一种流行策略。在此类研究中，学者们在每个地点开展因果研究，并评估研究发现是否可跨地点推广。尽管具有潜力，但对于一个基础性研究设计问题——我们应如何为外部效度选择地点——仍缺乏指导。现有方法存在挑战：随机抽取地点往往不可行，而当前目的性抽样的做法在缺乏统计保证的情况下并非最优。我们提出合成目的性抽样（SPS），它能为外部效度最优地选择多样化的地点。SPS结合了目的性抽样与合成控制法的思想——它选择多样化的地点，使得未被选中的地点能够由所选地点的加权平均值很好地近似。我们通过实验研究和观察性研究展示其普遍适用性。总体而言，本文为设计面向外部效度的多地点研究提供了新的统计基础。
关键词
多地点研究、外部效度、地点选择、合成目的性抽样、合成控制法、因果推断、研究设计