{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T05:05:47Z","timestamp":1772773547571,"version":"3.50.1"},"reference-count":34,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2024,1,31]],"date-time":"2024-01-31T00:00:00Z","timestamp":1706659200000},"content-version":"vor","delay-in-days":176,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2023,8,8]],"date-time":"2023-08-08T00:00:00Z","timestamp":1691452800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000050","name":"National Heart, Lung, and Blood Institute","doi-asserted-by":"publisher","award":["HL141286"],"award-info":[{"award-number":["HL141286"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000897","name":"Cystic Fibrosis Foundation","doi-asserted-by":"publisher","award":["SZCZES18Y7"],"award-info":[{"award-number":["SZCZES18Y7"]}],"id":[{"id":"10.13039\/100000897","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["5UL1TR001425-03"],"award-info":[{"award-number":["5UL1TR001425-03"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006093","name":"Patient-Centered Outcomes Research Institute","doi-asserted-by":"publisher","award":["ME-1408-19894"],"award-info":[{"award-number":["ME-1408-19894"]}],"id":[{"id":"10.13039\/100006093","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000050","name":"National Heart, Lung, and Blood Institute","doi-asserted-by":"publisher","award":["HL141286"],"award-info":[{"award-number":["HL141286"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000897","name":"Cystic Fibrosis Foundation","doi-asserted-by":"publisher","award":["SZCZES18Y7"],"award-info":[{"award-number":["SZCZES18Y7"]}],"id":[{"id":"10.13039\/100000897","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["5UL1TR001425-03"],"award-info":[{"award-number":["5UL1TR001425-03"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006093","name":"Patient-Centered Outcomes Research Institute","doi-asserted-by":"publisher","award":["ME-1408-19894"],"award-info":[{"award-number":["ME-1408-19894"]}],"id":[{"id":"10.13039\/100006093","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Missing data are a pervasive issue in observational studies using electronic health records or patient registries. It presents unique challenges for statistical inference, especially causal inference. Inappropriately handling missing data in causal inference could potentially bias causal estimation. Besides missing data problems, observational health data structures typically have mixed-type variables - continuous and categorical covariates - whose joint distribution is often too complex to be modeled by simple parametric models. The existence of missing values in covariates and outcomes makes the causal inference even more challenging, while most standard causal inference approaches assume fully observed data or start their works after imputing missing values in a separate preprocessing stage. To address these problems, we introduce a Bayesian nonparametric causal model to estimate causal effects with missing data. The proposed approach can simultaneously impute missing values, account for multiple outcomes, and estimate causal effects under the potential outcomes framework. We provide three simulation studies to show the performance of our proposed method under complicated data settings whose features are similar to our case studies. For example, Simulation Study 3 assumes the case where missing values exist in both outcomes and covariates. Two case studies were conducted applying our method to evaluate the comparative effectiveness of treatments for chronic disease management in juvenile idiopathic arthritis and cystic fibrosis.<\/jats:p>","DOI":"10.1111\/biom.13918","type":"journal-article","created":{"date-parts":[[2023,8,9]],"date-time":"2023-08-09T04:25:25Z","timestamp":1691555125000},"page":"3624-3636","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Bayesian Causal Inference for Observational Studies with Missingness in Covariates and Outcomes"],"prefix":"10.1093","volume":"79","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8550-3827","authenticated-orcid":false,"given":"Huaiyu","family":"Zang","sequence":"first","affiliation":[{"name":"Heart Institute, Cincinnati Children's Hospital Medical Center , Cincinnati, Ohio , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2029-2293","authenticated-orcid":false,"given":"Hang J.","family":"Kim","sequence":"additional","affiliation":[{"name":"Division of Statistics and Data Science, University of Cincinnati , Cincinnati, Ohio , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Huang","sequence":"additional","affiliation":[{"name":"Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center , Cincinnati, Ohio , USA"},{"name":"Department of Pediatrics, University of Cincinnati , Cincinnati, Ohio , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0705-715X","authenticated-orcid":false,"given":"Rhonda","family":"Szczesniak","sequence":"additional","affiliation":[{"name":"Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center , Cincinnati, Ohio , USA"},{"name":"Department of Pediatrics, University of Cincinnati , Cincinnati, Ohio , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2023,8,8]]},"reference":[{"key":"2024020107192308700_biom13918-bib-0001","volume-title":"Cystic Fibrosis Foundation Patient Registry 2019 annual data report","author":"Cystic Fibrosis Foundation","year":"2020"},{"key":"2024020107192308700_biom13918-bib-0002","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1080\/01621459.2000.10474263","article-title":"Estimating and using propensity scores with partially missing data","volume":"95","author":"D'Agostino","year":"2000","journal-title":"Journal of the American Statistical Association"},{"key":"2024020107192308700_biom13918-bib-0003","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1214\/16-BA1020","article-title":"Bayesian mixture models with focused clustering for mixed ordinal and nominal data","volume":"12","author":"DeYoreo","year":"2017","journal-title":"Bayesian Analysis"},{"key":"2024020107192308700_biom13918-bib-0004","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s41512-020-00077-0","article-title":"Informative missingness in electronic health record systems: the curse of knowing","volume":"4","author":"Groenwold","year":"2020","journal-title":"Diagnostic and Prognostic Research"},{"key":"2024020107192308700_biom13918-bib-0005","doi-asserted-by":"crossref","first-page":"1218","DOI":"10.3899\/jrheum.120661","article-title":"Incidence and prevalence of juvenile idiopathic arthritis among children in a managed care population, 1996\u20132009","volume":"40","author":"Harrold","year":"2013","journal-title":"The Journal of Rheumatology"},{"key":"2024020107192308700_biom13918-bib-0006","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1198\/jcgs.2010.08162","article-title":"Bayesian nonparametric modeling for causal inference","volume":"20","author":"Hill","year":"2011","journal-title":"Journal of Computational and Graphical Statistics"},{"issue":"1","key":"2024020107192308700_biom13918-bib-0007","doi-asserted-by":"crossref","DOI":"10.1136\/rmdopen-2019-001091","article-title":"Timing matters: real-world effectiveness of early combination of biologic and conventional synthetic disease-modifying antirheumatic drugs for treating newly diagnosed polyarticular course juvenile idiopathic arthritis","volume":"6","author":"Huang","year":"2020","journal-title":"RMD Open"},{"key":"2024020107192308700_biom13918-bib-0008","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9781139025751","volume-title":"Causal inference in statistics, social, and biomedical sciences","author":"Imbens","year":"2015"},{"key":"2024020107192308700_biom13918-bib-0009","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1198\/016214501750332758","article-title":"Gibbs sampling methods for stick-breaking priors","volume":"96","author":"Ishwaran","year":"2001","journal-title":"Journal of the American Statistical Association"},{"key":"2024020107192308700_biom13918-bib-0010","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1111\/rssc.12464","article-title":"Bayesian semi-parametric G-computation for causal inference in a cohort study with MNAR dropout and death","volume":"70","author":"Josefsson","year":"2021","journal-title":"Journal of the Royal Statistical Society. Series C, Applied statistics"},{"key":"2024020107192308700_biom13918-bib-0011","first-page":"523","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":"2024020107192308700_biom13918-bib-0012","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v070.i04","article-title":"bartMachine: machine learning with Bayesian additive regression trees","volume":"70","author":"Kapelner","year":"2016","journal-title":"Journal of Statistical Software"},{"key":"2024020107192308700_biom13918-bib-0013","doi-asserted-by":"crossref","first-page":"1173","DOI":"10.1513\/AnnalsATS.201511-781OC","article-title":"The Cystic Fibrosis Foundation Patient Registry. Design and methods of a national observational disease registry","volume":"13","author":"Knapp","year":"2016","journal-title":"Annals of the American Thoracic Society"},{"key":"2024020107192308700_biom13918-bib-0014","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1177\/0962280217713032","article-title":"Propensity score analysis with partially observed covariates: How should multiple imputation be used?","volume":"28","author":"Leyrat","year":"2019","journal-title":"Statistical Methods in Medical Research"},{"key":"2024020107192308700_biom13918-bib-0015","first-page":"2005","article-title":"Propensity score matching analysis for causal effects with MNAR covariates","volume":"28","author":"Lu","year":"2018","journal-title":"Statistica Sinica"},{"key":"2024020107192308700_biom13918-bib-0016","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v009.i08","article-title":"Analysis of complex survey samples","volume":"9","author":"Lumley","year":"2004","journal-title":"Journal of Statistical Software"},{"key":"2024020107192308700_biom13918-bib-0017","first-page":"50","volume-title":"ASA proceedings of the section on Bayesian statistical science","author":"MacEachern","year":"1999"},{"key":"2024020107192308700_biom13918-bib-0018","doi-asserted-by":"crossref","first-page":"1409","DOI":"10.1214\/20-AOAS1356","article-title":"Doubly robust treatment effect estimation with missing attributes","volume":"14","author":"Mayer","year":"2020","journal-title":"The Annals of Applied Statistics"},{"key":"2024020107192308700_biom13918-bib-0019","doi-asserted-by":"crossref","first-page":"4243","DOI":"10.1200\/JCO.2012.42.8011","article-title":"Importance of health information technology, electronic health records, and continuously aggregating data to comparative effectiveness research and learning health care","volume":"30","author":"Miriovsky","year":"2012","journal-title":"Journal of Clinical Oncology"},{"key":"2024020107192308700_biom13918-bib-0020","doi-asserted-by":"crossref","first-page":"1466","DOI":"10.1080\/01621459.2016.1174132","article-title":"Multiple imputation of missing categorical and continuous values via Bayesian mixture models with local dependence","volume":"111","author":"Murray","year":"2016","journal-title":"Journal of the American Statistical Association"},{"key":"2024020107192308700_biom13918-bib-0021","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1080\/01621459.1984.10478078","article-title":"Reducing bias in observational studies using subclassification on the propensity score","volume":"79","author":"Rosenbaum","year":"1984","journal-title":"Journal of the American Statistical Association"},{"key":"2024020107192308700_biom13918-bib-0022","doi-asserted-by":"crossref","first-page":"1193","DOI":"10.1111\/biom.12875","article-title":"Bayesian nonparametric generative models for causal inference with missing at random covariates","volume":"74","author":"Roy","year":"2018","journal-title":"Biometrics"},{"key":"2024020107192308700_biom13918-bib-0023","doi-asserted-by":"crossref","first-page":"688","DOI":"10.1037\/h0037350","article-title":"Estimating causal effects of treatments in randomized and nonrandomized studies","volume":"66","author":"Rubin","year":"1974","journal-title":"Journal of Educational Psychology"},{"key":"2024020107192308700_biom13918-bib-0024","doi-asserted-by":"crossref","DOI":"10.1002\/9780470316696","volume-title":"Multiple imputation for nonresponse in surveys","author":"Rubin","year":"1987"},{"key":"2024020107192308700_biom13918-bib-0025","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1002\/ppul.21521","article-title":"Reduced mortality in cystic fibrosis patients treated with tobramycin inhalation solution","volume":"47","author":"Sawicki","year":"2012","journal-title":"Pediatric Pulmonology"},{"key":"2024020107192308700_biom13918-bib-0026","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.jcf.2017.01.002","article-title":"Use of fev1 in cystic fibrosis epidemiologic studies and clinical trials: a statistical perspective for the clinical researcher","volume":"16","author":"Szczesniak","year":"2017","journal-title":"Journal of Cystic Fibrosis"},{"key":"2024020107192308700_biom13918-bib-0027","volume-title":"The Comprehensive R Archive Network","author":"The bartCause package","year":"2023"},{"key":"2024020107192308700_biom13918-bib-0028","volume-title":"The Comprehensive R Archive Network","author":"The WeightIt package","year":"2023"},{"key":"2024020107192308700_biom13918-bib-0029","doi-asserted-by":"crossref","DOI":"10.1201\/9780429492259","volume-title":"Flexible imputation of missing data","author":"van Buuren","year":"2018"},{"key":"2024020107192308700_biom13918-bib-0030","first-page":"1","article-title":"mice: Multivariate imputation by chained equations in R","volume":"45","author":"van Buuren","year":"2011","journal-title":"Journal of Statistical Software"},{"key":"2024020107192308700_biom13918-bib-0031","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2202\/1544-6115.1309","article-title":"Super learner","volume":"6","author":"van der Laan","year":"2007","journal-title":"Statistical Applications in Genetics and Molecular Biology"},{"key":"2024020107192308700_biom13918-bib-0032","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4419-9782-1","volume-title":"Targeted learning: causal inference for observational and experimental data","author":"van der Laan","year":"2011"},{"key":"2024020107192308700_biom13918-bib-0033","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2202\/1557-4679.1043","article-title":"Targeted maximum likelihood learning","volume":"2","author":"van der Laan","year":"2006","journal-title":"The International Journal of Biostatistics"},{"key":"2024020107192308700_biom13918-bib-0034","doi-asserted-by":"crossref","first-page":"875","DOI":"10.1093\/biomet\/asz048","article-title":"Causal inference with confounders missing not at random","volume":"106","author":"Yang","year":"2019","journal-title":"Biometrika"}],"container-title":["Biometrics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/biometrics\/article-pdf\/79\/4\/3624\/56396470\/biometrics_79_4_3624.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/biometrics\/article-pdf\/79\/4\/3624\/56396470\/biometrics_79_4_3624.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T07:22:37Z","timestamp":1706772157000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/biometrics\/article\/79\/4\/3624\/7587588"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,8]]},"references-count":34,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,8,8]]},"published-print":{"date-parts":[[2023,12,1]]}},"URL":"https:\/\/doi.org\/10.1111\/biom.13918","relation":{},"ISSN":["0006-341X","1541-0420"],"issn-type":[{"value":"0006-341X","type":"print"},{"value":"1541-0420","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2023,12]]},"published":{"date-parts":[[2023,8,8]]},"assertion":[{"value":"2022-08-05","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-07-13","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-08-08","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}