{
  "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.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Political Science and Statistics and Data Science Center Massachusetts Institute of Technology Cambridge Massachusetts USA",
    "Columbia University",
    "Center for the Study of Democratic Institutions Vanderbilt University Nashville Tennessee USA",
    "Columbia University - Department of Political Science"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Naoki Egami",
      "orcid": "0000-0002-5491-2174"
    },
    {
      "affs": [
        2,
        3
      ],
      "name": "Diana Da In Lee",
      "orcid": "0000-0002-1590-6644"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6mt02f2ztsbrc.bib",
  "cited_by": 8,
  "doi": "10.1111/ajps.70070",
  "fulltext_url": null,
  "id": "6mt02f2ztsbrc",
  "issns": [
    "0092-5853",
    "1540-5907"
  ],
  "landing_url": "https://doi.org/10.1111/ajps.70070",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2613|Advanced Causal Inference Techniques"
    ]
  ],
  "openalex": "W4392251943",
  "pdf_url": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/ajps.70070",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-07",
  "publisher": "Wiley",
  "ris": "https://research.draconitic.com/paper/6mt02f2ztsbrc.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:17Z",
      "native_id": "W4392251943",
      "source": "openalex",
      "url": "https://doi.org/10.1111/ajps.70070"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "openalex:2613|Advanced Causal Inference Techniques",
      "subfield": "statistics"
    }
  ],
  "title": "Designing multi‐site studies for external validity: Site selection via synthetic purposive sampling",
  "title_text": "Designing multi‐site studies for external validity: Site selection via synthetic purposive sampling",
  "type": "peer-reviewed",
  "updated_at": "2026-11-06T13:20:21Z",
  "url": "https://research.draconitic.com/paper/6mt02f2ztsbrc",
  "venue": "American Journal of Political Science",
  "versions": []
}