These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
142 related articles for article (PubMed ID: 36131394)
1. Case studies in bias reduction and inference for electronic health record data with selection bias and phenotype misclassification. Beesley LJ; Mukherjee B Stat Med; 2022 Dec; 41(28):5501-5516. PubMed ID: 36131394 [TBL] [Abstract][Full Text] [Related]
2. Bias reduction and inference for electronic health record data under selection and phenotype misclassification: three case studies. Beesley LJ; Mukherjee B medRxiv; 2020 Dec; ():. PubMed ID: 33398299 [TBL] [Abstract][Full Text] [Related]
3. Statistical inference for association studies using electronic health records: handling both selection bias and outcome misclassification. Beesley LJ; Mukherjee B Biometrics; 2022 Mar; 78(1):214-226. PubMed ID: 33179768 [TBL] [Abstract][Full Text] [Related]
4. A framework for understanding selection bias in real-world healthcare data. Kundu R; Shi X; Morrison J; Barrett J; Mukherjee B J R Stat Soc Ser A Stat Soc; 2024 Aug; 187(3):606-635. PubMed ID: 39281782 [TBL] [Abstract][Full Text] [Related]
5. An analytic framework for exploring sampling and observation process biases in genome and phenome-wide association studies using electronic health records. Beesley LJ; Fritsche LG; Mukherjee B Stat Med; 2020 Jun; 39(14):1965-1979. PubMed ID: 32198773 [TBL] [Abstract][Full Text] [Related]
6. Adjusting for selection bias due to missing data in electronic health records-based research. Peskoe SB; Arterburn D; Coleman KJ; Herrinton LJ; Daniels MJ; Haneuse S Stat Methods Med Res; 2021 Oct; 30(10):2221-2238. PubMed ID: 34445911 [TBL] [Abstract][Full Text] [Related]
7. Prevalence estimation by joint use of big data and health survey: a demonstration study using electronic health records in New York city. Kim RS; Shankar V BMC Med Res Methodol; 2020 Apr; 20(1):77. PubMed ID: 32252642 [TBL] [Abstract][Full Text] [Related]
8. Addressing Information Biases Within Electronic Health Record Data to Improve the Examination of Epidemiologic Associations With Diabetes Prevalence Among Young Adults: Cross-Sectional Study. Conderino S; Anthopolos R; Albrecht SS; Farley SM; Divers J; Titus AR; Thorpe LE JMIR Med Inform; 2024 Oct; 12():e58085. PubMed ID: 39353204 [TBL] [Abstract][Full Text] [Related]
9. To weight or not to weight? The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice. Salvatore M; Kundu R; Shi X; Friese CR; Lee S; Fritsche LG; Mondul AM; Hanauer D; Pearce CL; Mukherjee B J Am Med Inform Assoc; 2024 Jun; 31(7):1479-1492. PubMed ID: 38742457 [TBL] [Abstract][Full Text] [Related]
10. A method for cohort selection of cardiovascular disease records from an electronic health record system. Abrahão MTF; Nobre MRC; Gutierrez MA Int J Med Inform; 2017 Jun; 102():138-149. PubMed ID: 28495342 [TBL] [Abstract][Full Text] [Related]
11. Integration of genetic and clinical information to improve imputation of data missing from electronic health records. Li R; Chen Y; Moore JH J Am Med Inform Assoc; 2019 Oct; 26(10):1056-1063. PubMed ID: 31329892 [TBL] [Abstract][Full Text] [Related]
12. PIE: A prior knowledge guided integrated likelihood estimation method for bias reduction in association studies using electronic health records data. Huang J; Duan R; Hubbard RA; Wu Y; Moore JH; Xu H; Chen Y J Am Med Inform Assoc; 2018 Mar; 25(3):345-352. PubMed ID: 29206922 [TBL] [Abstract][Full Text] [Related]
13. An augmented estimation procedure for EHR-based association studies accounting for differential misclassification. Tong J; Huang J; Chubak J; Wang X; Moore JH; Hubbard RA; Chen Y J Am Med Inform Assoc; 2020 Feb; 27(2):244-253. PubMed ID: 31617899 [TBL] [Abstract][Full Text] [Related]
14. PATIENT RECRUITMENT USING ELECTRONIC HEALTH RECORDS UNDER SELECTION BIAS: A TWO-PHASE SAMPLING FRAMEWORK. Zhang G; Beesley LJ; Mukherjee B; Shi XU Ann Appl Stat; 2024 Sep; 18(3):1858-1878. PubMed ID: 39149424 [TBL] [Abstract][Full Text] [Related]
15. Reducing Bias Due to Outcome Misclassification for Epidemiologic Studies Using EHR-derived Probabilistic Phenotypes. Hubbard RA; Tong J; Duan R; Chen Y Epidemiology; 2020 Jul; 31(4):542-550. PubMed ID: 32282406 [TBL] [Abstract][Full Text] [Related]
16. A Quantitative Bias Analysis Approach to Informative Presence Bias in Electronic Health Records. Zhang H; Clark AS; Hubbard RA Epidemiology; 2024 May; 35(3):349-358. PubMed ID: 38630509 [TBL] [Abstract][Full Text] [Related]
18. Can the Use of Bayesian Analysis Methods Correct for Incompleteness in Electronic Health Records Diagnosis Data? Development of a Novel Method Using Simulated and Real-Life Clinical Data. Ford E; Rooney P; Hurley P; Oliver S; Bremner S; Cassell J Front Public Health; 2020; 8():54. PubMed ID: 32211363 [No Abstract] [Full Text] [Related]
19. Adult patient access to electronic health records. Ammenwerth E; Neyer S; Hörbst A; Mueller G; Siebert U; Schnell-Inderst P Cochrane Database Syst Rev; 2021 Feb; 2(2):CD012707. PubMed ID: 33634854 [TBL] [Abstract][Full Text] [Related]