Bayesian analysis of pair‐matched case‐control studies subject to outcome misclassification
We examine the impact of nondifferential outcome misclassification on odds ratios estimated from pair‐matched case‐control studies and propose a Bayesian model to adjust these estimates for misclassification bias. The model relies on access to a validation subgroup with confirmed outcome status for...
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| Published in | Statistics in medicine Vol. 36; no. 26; pp. 4196 - 4213 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Wiley Subscription Services, Inc
20.11.2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0277-6715 1097-0258 1097-0258 |
| DOI | 10.1002/sim.7427 |
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| Abstract | We examine the impact of nondifferential outcome misclassification on odds ratios estimated from pair‐matched case‐control studies and propose a Bayesian model to adjust these estimates for misclassification bias. The model relies on access to a validation subgroup with confirmed outcome status for all case‐control pairs as well as prior knowledge about the positive and negative predictive value of the classification mechanism. We illustrate the model's performance on simulated data and apply it to a database study examining the presence of ten morbidities in the prodromal phase of multiple sclerosis. |
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| AbstractList | We examine the impact of nondifferential outcome misclassification on odds ratios estimated from pair-matched case-control studies and propose a Bayesian model to adjust these estimates for misclassification bias. The model relies on access to a validation subgroup with confirmed outcome status for all case-control pairs as well as prior knowledge about the positive and negative predictive value of the classification mechanism. We illustrate the model's performance on simulated data and apply it to a database study examining the presence of ten morbidities in the prodromal phase of multiple sclerosis.We examine the impact of nondifferential outcome misclassification on odds ratios estimated from pair-matched case-control studies and propose a Bayesian model to adjust these estimates for misclassification bias. The model relies on access to a validation subgroup with confirmed outcome status for all case-control pairs as well as prior knowledge about the positive and negative predictive value of the classification mechanism. We illustrate the model's performance on simulated data and apply it to a database study examining the presence of ten morbidities in the prodromal phase of multiple sclerosis. We examine the impact of nondifferential outcome misclassification on odds ratios estimated from pair‐matched case‐control studies and propose a Bayesian model to adjust these estimates for misclassification bias. The model relies on access to a validation subgroup with confirmed outcome status for all case‐control pairs as well as prior knowledge about the positive and negative predictive value of the classification mechanism. We illustrate the model's performance on simulated data and apply it to a database study examining the presence of ten morbidities in the prodromal phase of multiple sclerosis. |
| Author | Petkau, John Wijnands, José MA Gustafson, Paul Högg, Tanja Zhao, Yinshan Tremlett, Helen |
| Author_xml | – sequence: 1 givenname: Tanja orcidid: 0000-0002-1448-9818 surname: Högg fullname: Högg, Tanja email: thoegg@stat.ubc.ca organization: University of British Columbia – sequence: 2 givenname: John surname: Petkau fullname: Petkau, John organization: University of British Columbia – sequence: 3 givenname: Yinshan surname: Zhao fullname: Zhao, Yinshan organization: BC Centre for Improved Cardiovascular Health – sequence: 4 givenname: Paul orcidid: 0000-0002-2375-5006 surname: Gustafson fullname: Gustafson, Paul organization: University of British Columbia – sequence: 5 givenname: José MA surname: Wijnands fullname: Wijnands, José MA organization: University of British Columbia – sequence: 6 givenname: Helen surname: Tremlett fullname: Tremlett, Helen organization: University of British Columbia |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28783882$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1007/s10654-006-9078-x 10.1093/oxfordjournals.aje.a115630 10.1016/S0895-4356(03)00246-4 10.24095/hpcdp.34.2/3.09 10.1007/978-1-4899-4477-1 10.2307/2531093 10.1164/rccm.201211-2004OC 10.1002/0471249688 10.1093/oxfordjournals.aje.a009251 10.1023/A:1008929526011 10.1093/ije/12.1.93 10.1016/j.annepidem.2012.12.007 10.1093/biomet/84.3.523 10.1093/aje/kws340 10.1177/1471082X0700700303 10.1002/sim.1477 10.1214/ss/1177011136 10.1002/sim.3971 10.1002/sim.1546 10.1093/oxfordjournals.aje.a113424 10.1201/9780203502761 10.1002/sim.3694 10.1002/sim.1656 10.1002/sim.2000 10.1017/S0317167100015961 10.1093/rheumatology/kes353 10.1007/s00415-015-7842-0 10.1212/WNL.0b013e3181cf6ec0 |
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| Keywords | matched case-control study odds ratio Bayesian method health administrative databases outcome misclassification |
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| Snippet | We examine the impact of nondifferential outcome misclassification on odds ratios estimated from pair‐matched case‐control studies and propose a Bayesian model... We examine the impact of nondifferential outcome misclassification on odds ratios estimated from pair-matched case-control studies and propose a Bayesian model... |
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| SubjectTerms | Bayes Theorem Bayesian analysis Bayesian method Bias British Columbia Case-Control Studies Comorbidity Computer Simulation Data Interpretation, Statistical Databases, Factual health administrative databases Humans matched case‐control study Morbidity Multiple sclerosis Multiple Sclerosis - complications Odds Ratio outcome misclassification |
| Title | Bayesian analysis of pair‐matched case‐control studies subject to outcome misclassification |
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