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Linking EHRs to other data sources with higher\u2010quality measurements can improve statistical inference, but such analyses must account for selection bias if the linked data source arises from a non\u2010probability sample. We propose a set of novel estimators targeting the average treatment effect (ATE) that combine information from binary outcomes measured with error in a large, population\u2010representative EHR database with gold\u2010standard outcomes obtained from a smaller validation sample subject to selection bias. We evaluate our approach in extensive simulations and an analysis of data from the Adult Changes in Thought (ACT) study, a longitudinal study of incident dementia in a cohort of Kaiser Permanente Washington members with linked EHR data. For a subset of deceased ACT participants who consented to brain autopsy prior to death, gold\u2010standard measures of Alzheimer's disease neuropathology are available. Our proposed estimators reduced bias and improved efficiency for the ATE, facilitating valid inference with EHR data when key data elements are ascertained with error.<\/jats:p>","DOI":"10.1002\/sim.70127","type":"journal-article","created":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T10:39:20Z","timestamp":1752575960000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Integrating Misclassified EHR Outcomes With Validated Outcomes From a Non\u2010Probability Sample"],"prefix":"10.1002","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8629-7201","authenticated-orcid":false,"given":"Jenny","family":"Shen","sequence":"first","affiliation":[{"name":"Department of Biostatistics, Epidemiology, and Informatics Perelman School of Medicine, University of Pennsylvania  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dane","family":"Isenberg","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology, and Informatics Perelman School of Medicine, University of Pennsylvania  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristin A.","family":"Linn","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology, and Informatics Perelman School of Medicine, University of Pennsylvania  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rebecca A.","family":"Hubbard","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Brown University School of Public Health  Providence Rhode Island USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,7,15]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.7326\/M19-0873"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00125-017-4518-6"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1377\/hlthaff.2014.0453"},{"key":"e_1_2_9_5_1","article-title":"Biases in Electronic Health Record Data due to Processes Within the Healthcare System: Retrospective Observational Study","volume":"361","author":"Agniel D.","year":"2018","journal-title":"BMJ"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.9134"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.13063\/2327-9214.1079"},{"key":"e_1_2_9_8_1","first-page":"3","volume-title":"Modern Statistical Methods for Health Research","author":"Hubbard R. 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