Using overlap weights to address extreme propensity scores in estimating restricted mean counterfactual survival times.

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Title: Using overlap weights to address extreme propensity scores in estimating restricted mean counterfactual survival times.
Authors: Cao Z; Department of Mathematics, College of Big Data and Internet, Shenzhen Technology University, Guangdong, China., Ghazi L; Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States., Mastrogiacomo C; Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States.; Center for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT, United States., Forastiere L; Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States.; Center for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT, United States., Wilson FP; Clinical and Translational Research Accelerator, Department of Medicine, Yale School of Medicine, New Haven, CT, United States., Li F; Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States.; Center for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT, United States.; Clinical and Translational Research Accelerator, Department of Medicine, Yale School of Medicine, New Haven, CT, United States.
Source: American journal of epidemiology [Am J Epidemiol] 2025 Aug 05; Vol. 194 (8), pp. 2402-2411.
Publication Type: Journal Article
Journal Info: Publisher: Oxford University Press Country of Publication: United States NLM ID: 7910653 Publication Model: Print Cited Medium: Internet ISSN: 1476-6256 (Electronic) Linking ISSN: 00029262 NLM ISO Abbreviation: Am J Epidemiol Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Cao+Z%22">Cao Z</searchLink>; Department of Mathematics, College of Big Data and Internet, Shenzhen Technology University, Guangdong, China.<br /><searchLink fieldCode="AU" term="%22Ghazi+L%22">Ghazi L</searchLink>; Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States.<br /><searchLink fieldCode="AU" term="%22Mastrogiacomo+C%22">Mastrogiacomo C</searchLink>; Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States.; Center for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT, United States.<br /><searchLink fieldCode="AU" term="%22Forastiere+L%22">Forastiere L</searchLink>; Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States.; Center for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT, United States.<br /><searchLink fieldCode="AU" term="%22Wilson+FP%22">Wilson FP</searchLink>; Clinical and Translational Research Accelerator, Department of Medicine, Yale School of Medicine, New Haven, CT, United States.<br /><searchLink fieldCode="AU" term="%22Li+F%22">Li F</searchLink>; Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States.; Center for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT, United States.; Clinical and Translational Research Accelerator, Department of Medicine, Yale School of Medicine, New Haven, CT, United States.
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        Value: 10.1093/aje/kwae416
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        Text: English
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              Text: 2025 Aug 05
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