Targeted Treatment Assignment Using Data from Randomized Experiments with Noncompliance.
This paper considers randomized experiments with noncompliance where individuals in the treatment group become eligible for a treatment but some do not receive it. We study the estimation and evaluation of treatment assignment policies targeted to individuals on the basis of pretreatment characteris...
| Publicado en: | AEA Papers & Proceedings Vol. 115; pp. 209 - 215 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
American Economic Association
May2025
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=185592628&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 185592628 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 25740768 LNGQ jtl: AEA Papers & Proceedings issn: 25740768 maglogo: N pubinfo: dt: May2025 vid: 115 pid: 22 pub: American Economic Association artinfo: ui: 185592628 10.1257/pandp.20251063 ppf: 209 ppct: 6 formats: tig: atl: Targeted Treatment Assignment Using Data from Randomized Experiments with Noncompliance. aug: au: Athey, Susan Inoue, Kosuke Tsugawa, Yusuke affil: Stanford University Kyoto University University of California, Los Angeles su: Clinical trials Noncompliance Treatment effectiveness Statistical decision making Assignment problems (Programming) sug: subj: Clinical trials Research and Development in the Physical, Engineering, and Life Sciences (except Biotechnology) Noncompliance Treatment effectiveness Statistical decision making Assignment problems (Programming) ab: This paper considers randomized experiments with noncompliance where individuals in the treatment group become eligible for a treatment but some do not receive it. We study the estimation and evaluation of treatment assignment policies targeted to individuals on the basis of pretreatment characteristics. We consider a decision problem where the policy determines eligibility, which is costly, and compliance continues to be imperfect. Then optimal policies prioritize by a weighted average of the intent-to-treat effect of eligibility on outcomes and the treatment effect of eligibility on receiving the treatment. We illustrate the ideas using data from the Oregon Health Insurance Experiment. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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