{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T14:02:30Z","timestamp":1791986550330,"version":"4.4.0"},"reference-count":34,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2023,2,17]],"date-time":"2023-02-17T00:00:00Z","timestamp":1676592000000},"content-version":"vor","delay-in-days":3067,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000001","name":"US National Science Foundation","doi-asserted-by":"publisher","award":["DMS-1107004"],"award-info":[{"award-number":["DMS-1107004"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"US National Science Foundation","doi-asserted-by":"publisher","award":["DMS-1107070"],"award-info":[{"award-number":["DMS-1107070"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,9,1]]},"abstract":"<jats:title>Summary<\/jats:title>\n                  <jats:p>A framework for causal inference from two-level factorial designs is proposed, which uses potential outcomes to define causal effects. The paper explores the effect of non-additivity of unit level treatment effects on Neyman's repeated sampling approach for estimation of causal effects and on Fisher's randomization tests on sharp null hypotheses in these designs. The framework allows for statistical inference from a finite population, permits definition and estimation of estimands other than \u2018average factorial effects\u2019 and leads to more flexible inference procedures than those based on ordinary least squares estimation from a linear model.<\/jats:p>","DOI":"10.1111\/rssb.12085","type":"journal-article","created":{"date-parts":[[2014,9,25]],"date-time":"2014-09-25T03:15:15Z","timestamp":1411614915000},"page":"727-753","source":"Crossref","is-referenced-by-count":70,"title":["Causal Inference from 2K Factorial Designs by Using Potential Outcomes"],"prefix":"10.1093","volume":"77","author":[{"given":"Tirthankar","family":"Dasgupta","sequence":"first","affiliation":[{"name":"Harvard University , Cambridge , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Natesh S.","family":"Pillai","sequence":"additional","affiliation":[{"name":"Harvard University , Cambridge , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Donald B.","family":"Rubin","sequence":"additional","affiliation":[{"name":"Harvard University , Cambridge , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2014,9,25]]},"reference":[{"key":"2023021801091460700_rssb12085-cit-0001","doi-asserted-by":"crossref","first-page":"214","DOI":"10.2307\/2981920","article-title":"A unified approach to design of experiments","volume":"144","author":"Bailey","year":"1981","journal-title":"J. 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