{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T05:22:46Z","timestamp":1786684966013,"version":"build-2736575974"},"reference-count":58,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2024,3,4]],"date-time":"2024-03-04T00:00:00Z","timestamp":1709510400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000009","name":"NIH","doi-asserted-by":"publisher","award":["grants R01AI27271, R01CA222147, R01AG065276, and R01GM139926"],"award-info":[{"award-number":["grants R01AI27271, R01CA222147, R01AG065276, and R01GM139926"]}],"id":[{"id":"10.13039\/100000009","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,9,13]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Conformal prediction has received tremendous attention in recent years and has offered new solutions to problems in missing data and causal inference; yet these advances have not leveraged modern semi-parametric efficiency theory for more efficient uncertainty quantification. We consider the problem of obtaining well-calibrated prediction regions that can data adaptively account for a shift in the distribution of covariates between training and test data. Under a covariate shift assumption analogous to the standard missing at random assumption, we propose a general framework based on efficient influence functions to construct well-calibrated prediction regions for the unobserved outcome in the test sample without compromising coverage.<\/jats:p>","DOI":"10.1093\/jrsssb\/qkae009","type":"journal-article","created":{"date-parts":[[2024,3,4]],"date-time":"2024-03-04T20:39:29Z","timestamp":1709584769000},"page":"943-965","source":"Crossref","is-referenced-by-count":23,"title":["Doubly robust calibration of prediction sets under covariate shift"],"prefix":"10.1093","volume":"86","author":[{"given":"Yachong","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Statistics & Data Science, University of Pennsylvania , Philadelphia, PA , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4459-5352","authenticated-orcid":false,"given":"Arun Kumar","family":"Kuchibhotla","sequence":"additional","affiliation":[{"name":"Department of Statistics & Data Science, Carnegie Mellon University , Pittsburgh, PA , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric","family":"Tchetgen Tchetgen","sequence":"additional","affiliation":[{"name":"Department of Statistics & Data Science, University of Pennsylvania , Philadelphia, PA , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,3,4]]},"reference":[{"issue":"4","key":"2024091323314045000_qkae009-B1","doi-asserted-by":"publisher","first-page":"962","DOI":"10.1111\/biom.2005.61.issue-4","article-title":"Doubly robust estimation in missing data and causal inference models","volume":"61","author":"Bang","year":"2005","journal-title":"Biometrics"},{"issue":"1","key":"2024091323314045000_qkae009-B2","doi-asserted-by":"publisher","first-page":"486","DOI":"10.1214\/20-AOS1965","article-title":"Predictive inference with the jackknife+","volume":"49","author":"Barber","year":"2021","journal-title":"The Annals of Statistics"},{"issue":"2","key":"2024091323314045000_qkae009-B3","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1093\/imaiai\/iaaa017","article-title":"The limits of distribution-free conditional predictive inference","volume":"10","author":"Barber","year":"2021","journal-title":"Information and Inference: A Journal of the IMA"},{"issue":"3","key":"2024091323314045000_qkae009-B4","doi-asserted-by":"publisher","first-page":"77","DOI":"10.2307\/2986806","article-title":"Statistical tolerance regions: Classical and Bayesian","volume":"20","author":"Bassett","year":"1971","journal-title":"Journal of the Royal Statistical Society Series D: The Statistician"},{"key":"2024091323314045000_qkae009-B5","volume-title":"Efficient and adaptive estimation for semiparametric models","author":"Bickel","year":"1993"},{"issue":"9","key":"2024091323314045000_qkae009-B6","first-page":"2137","article-title":"Discriminative learning under covariate shift","volume":"10","author":"Bickel","year":"2009","journal-title":"Journal of Machine Learning Research"},{"issue":"1","key":"2024091323314045000_qkae009-B7","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1093\/jrsssb\/qkac004","article-title":"Conformalized survival analysis","volume":"85","author":"Cand\u00e8s","year":"2023","journal-title":"Journal of the Royal Statistical Society Series B: Statistical Methodology"},{"key":"2024091323314045000_qkae009-B8","author":"Cauchois","year":"2020"},{"issue":"4","key":"2024091323314045000_qkae009-B9","doi-asserted-by":"publisher","first-page":"1541","DOI":"10.1214\/17-AOS1594","article-title":"Efficient and adaptive linear regression in semi-supervised settings","volume":"46","author":"Chakrabortty","year":"2018","journal-title":"The Annals of Statistics"},{"key":"2024091323314045000_qkae009-B10","author":"Chen","year":"2016"},{"issue":"3","key":"2024091323314045000_qkae009-B11","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1093\/biomet\/asp030","article-title":"Improving point and interval estimators of monotone functions by rearrangement","volume":"96","author":"Chernozhukov","year":"2009","journal-title":"Biometrika"},{"key":"2024091323314045000_qkae009-B120","author":"Guttman","year":"1970"},{"issue":"2\u20133","key":"2024091323314045000_qkae009-B12","first-page":"173","article-title":"Nearest neighbor based conformal prediction","volume":"63","author":"Gy\u00f4rfi","year":"2019","journal-title":"Annales de l'ISUP"},{"issue":"2","key":"2024091323314045000_qkae009-B13","doi-asserted-by":"publisher","first-page":"315","DOI":"10.2307\/2998560","article-title":"On the role of the propensity score in efficient semiparametric estimation of average treatment effects","volume":"66","author":"Hahn","year":"1998","journal-title":"Econometrica"},{"issue":"346","key":"2024091323314045000_qkae009-B14","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1080\/01621459.1974.10482962","article-title":"The influence curve and its role in robust estimation","volume":"69","author":"Hampel","year":"1974","journal-title":"Journal of the American Statistical Association"},{"issue":"6","key":"2024091323314045000_qkae009-B15","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2214889120","article-title":"Sensitivity analysis of individual treatment effects: A robust conformal inference approach","volume":"120","author":"Jin","year":"2023","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"4","key":"2024091323314045000_qkae009-B16","doi-asserted-by":"publisher","first-page":"523","DOI":"10.1214\/07-STS227","article-title":"Demystifying double robustness: A comparison of alternative strategies for estimating a population mean from incomplete data","volume":"22","author":"Kang","year":"2007","journal-title":"Statistical Science"},{"key":"2024091323314045000_qkae009-B17","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/3897.001.0001","volume-title":"An introduction to computational learning theory","author":"Kearns","year":"1994"},{"key":"2024091323314045000_qkae009-B18","article-title":"Predictive inference is free with the jackknife+-after-bootstrap","author":"Kim","year":"2020","journal-title":"Proceedings of the 34th international conference on Neural Information Processing Systems (NIPS'20)"},{"key":"2024091323314045000_qkae009-B19","author":"Kivaranovic","year":"2020"},{"key":"2024091323314045000_qkae009-B20","author":"Kpotufe","year":"2018"},{"key":"2024091323314045000_qkae009-B21","doi-asserted-by":"crossref","DOI":"10.1002\/9780470473900","volume-title":"Statistical tolerance regions: Theory, applications, and computation","author":"Krishnamoorthy","year":"2009"},{"key":"2024091323314045000_qkae009-B22","author":"Kuchibhotla","year":"2020"},{"issue":"1","key":"2024091323314045000_qkae009-B23","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1214\/22-AOAS1650","article-title":"Nested conformal prediction sets for classification with applications to probation data","volume":"17","author":"Kuchibhotla","year":"2023","journal-title":"The Annals of Applied Statistics"},{"issue":"523","key":"2024091323314045000_qkae009-B24","doi-asserted-by":"publisher","first-page":"1094","DOI":"10.1080\/01621459.2017.1307116","article-title":"Distribution-free predictive inference for regression","volume":"113","author":"Lei","year":"2018","journal-title":"Journal of the American Statistical Association"},{"issue":"501","key":"2024091323314045000_qkae009-B25","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1080\/01621459.2012.751873","article-title":"Distribution-free prediction sets","volume":"108","author":"Lei","year":"2013","journal-title":"Journal of the American Statistical Association"},{"issue":"1","key":"2024091323314045000_qkae009-B26","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1111\/rssb.12021","article-title":"Distribution-free prediction bands for non-parametric regression","volume":"76","author":"Lei","year":"2014","journal-title":"Journal of the Royal Statistical Society: Series B (Statistical Methodology)"},{"issue":"5","key":"2024091323314045000_qkae009-B27","doi-asserted-by":"publisher","first-page":"911","DOI":"10.1111\/rssb.12445","article-title":"Conformal inference of counterfactuals and individual treatment effects","volume":"83","author":"Lei","year":"2021","journal-title":"Journal of the Royal Statistical Society Series B: Statistical Methodology"},{"issue":"4","key":"2024091323314045000_qkae009-B28","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1198\/073500107000000250","article-title":"Nonparametric estimation of conditional CDF and quantile functions with mixed categorical and continuous data","volume":"26","author":"Li","year":"2008","journal-title":"Journal of Business & Economic Statistics"},{"issue":"3","key":"2024091323314045000_qkae009-B29","doi-asserted-by":"publisher","first-page":"1269","DOI":"10.1214\/aop\/1176990746","article-title":"The tight constant in the Dvoretzky-Kiefer-Wolfowitz inequality","volume":"18","author":"Massart","year":"1990","journal-title":"The Annals of Probability"},{"issue":"2","key":"2024091323314045000_qkae009-B30","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1002\/jae.v5:2","article-title":"Semiparametric efficiency bounds","volume":"5","author":"Newey","year":"1990","journal-title":"Journal of Applied Econometrics"},{"issue":"1","key":"2024091323314045000_qkae009-B31","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/S0304-4076(97)00011-0","article-title":"Convergence rates and asymptotic normality for series estimators","volume":"79","author":"Newey","year":"1997","journal-title":"Journal of Econometrics"},{"key":"2024091323314045000_qkae009-B32","author":"Papadopoulos","year":"2002"},{"key":"2024091323314045000_qkae009-B33","author":"Park","year":"2022"},{"key":"2024091323314045000_qkae009-B34","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1007\/978-3-0348-5513-6_12","article-title":"Investigating the quantile of an unknown distribution","volume":"22","author":"Pfanzagl","year":"1976","journal-title":"Ziegler, W.J. (ed) Contribution to Applied Statistics. Experientia Supplementum"},{"key":"2024091323314045000_qkae009-B35","author":"Polley","year":"2010"},{"issue":"5","key":"2024091323314045000_qkae009-B36","doi-asserted-by":"publisher","first-page":"1680","DOI":"10.1093\/jrsssb\/qkad069","article-title":"Prediction sets adaptive to unknown covariate shift","volume":"85","author":"Qiu","year":"2023","journal-title":"Journal of the Royal Statistical Society Series B: Statistical Methodology"},{"key":"2024091323314045000_qkae009-B37","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/9780262170055.001.0001","volume-title":"Dataset shift in machine learning","author":"Qui\u00f1onero-Candela","year":"2008"},{"issue":"1","key":"2024091323314045000_qkae009-B38","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/S0304-4076(03)00157-X","article-title":"Nonparametric estimation of regression functions with both categorical and continuous data","volume":"119","author":"Racine","year":"2004","journal-title":"Journal of Econometrics"},{"key":"2024091323314045000_qkae009-B39","doi-asserted-by":"publisher","author":"Reddi","year":"2015","DOI":"10.1609\/aaai.v29i1.9576"},{"issue":"6","key":"2024091323314045000_qkae009-B40","doi-asserted-by":"publisher","first-page":"3618","DOI":"10.1214\/21-AOS2102","article-title":"Adaptive transfer learning","volume":"49","author":"Reeve","year":"2021","journal-title":"The Annals of Statistics"},{"key":"2024091323314045000_qkae009-B41","author":"Robins","year":"2008"},{"key":"2024091323314045000_qkae009-B42","author":"Robins","year":"2000"},{"issue":"5","key":"2024091323314045000_qkae009-B43","doi-asserted-by":"publisher","first-page":"1951","DOI":"10.1214\/16-AOS1515","article-title":"Minimax estimation of a functional on a structured high-dimensional model","volume":"45","author":"Robins","year":"2017","journal-title":"The Annals of Statistics"},{"key":"2024091323314045000_qkae009-B44","author":"Romano","year":"2019"},{"key":"2024091323314045000_qkae009-B45","first-page":"3543","author":"Romano","year":"2020"},{"issue":"448","key":"2024091323314045000_qkae009-B46","doi-asserted-by":"publisher","first-page":"1096","DOI":"10.1080\/01621459.1999.10473862","article-title":"Adjusting for nonignorable drop-out using semiparametric nonresponse models","volume":"94","author":"Scharfstein","year":"1999","journal-title":"Journal of the American Statistical Association"},{"issue":"3","key":"2024091323314045000_qkae009-B47","doi-asserted-by":"publisher","first-page":"1514","DOI":"10.1214\/19-AOS1857","article-title":"The hardness of conditional independence testing and the generalised covariance measure","volume":"48","author":"Shah","year":"2020","journal-title":"The Annals of Statistics"},{"key":"2024091323314045000_qkae009-B48","doi-asserted-by":"publisher","first-page":"109395","DOI":"10.1016\/j.spl.2022.109395","article-title":"Multi split conformal prediction","volume":"184","author":"Solari","year":"2022","journal-title":"Statistics & Probability Letters"},{"issue":"1532\u20134435","key":"2024091323314045000_qkae009-B49","first-page":"985","article-title":"Covariate shift adaptation by importance weighted cross validation","volume":"8","author":"Sugiyama","year":"2007","journal-title":"Journal of Machine Learning Research"},{"key":"2024091323314045000_qkae009-B50","article-title":"Conformal prediction under covariate shift","author":"Tibshirani","year":"2019","journal-title":"Proceedings of the 33rd international conference on neural information processing systems"},{"key":"2024091323314045000_qkae009-B51","volume-title":"Asymptotic statistics","author":"van der Vaart","year":"2000"},{"key":"2024091323314045000_qkae009-B52","author":"van der Vaart","year":"2002"},{"key":"2024091323314045000_qkae009-B53","first-page":"475","author":"Vovk","year":"2012"},{"key":"2024091323314045000_qkae009-B54","volume-title":"Algorithmic learning in a random world","author":"Vovk","year":"2005"},{"key":"2024091323314045000_qkae009-B55","author":"Yang","year":"2021"},{"issue":"5","key":"2024091323314045000_qkae009-B56","doi-asserted-by":"publisher","first-page":"2538","DOI":"10.1214\/18-AOS1756","article-title":"Semi-supervised inference: General theory and estimation of means","volume":"47","author":"Zhang","year":"2019","journal-title":"The Annals of Statistics"},{"issue":"1","key":"2024091323314045000_qkae009-B57","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-031-01548-9","article-title":"Introduction to semi-supervised learning","volume":"3","author":"Zhu","year":"2009","journal-title":"Synthesis Lectures on Artificial Intelligence and Machine Learning"}],"container-title":["Journal of the Royal Statistical Society Series B: Statistical Methodology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/jrsssb\/article-pdf\/86\/4\/943\/59112644\/qkae009.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jrsssb\/article-pdf\/86\/4\/943\/59112644\/qkae009.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,14]],"date-time":"2024-09-14T08:17:51Z","timestamp":1726301871000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jrsssb\/article\/86\/4\/943\/7618755"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,4]]},"references-count":58,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2024,3,4]]},"published-print":{"date-parts":[[2024,9,13]]}},"URL":"https:\/\/doi.org\/10.1093\/jrsssb\/qkae009","relation":{},"ISSN":["1369-7412","1467-9868"],"issn-type":[{"value":"1369-7412","type":"print"},{"value":"1467-9868","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2024,9]]},"published":{"date-parts":[[2024,3,4]]}}}