Quantifying the impact of unmeasured confounding in observational studies with the E value
The E value method deals with unmeasured confounding, a key source of bias in observational studies. The E value method is described and its use is shown in a worked example of a meta-analysis examining the association between the use of antidepressants in pregnancy and the risk of miscarriage.
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2023-10-01
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| Series: | BMJ Medicine |
| Online Access: | https://bmjmedicine.bmj.com/content/2/1/e000366.full |
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| _version_ | 1850138361767919616 |
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| author | Irene Petersen Vera Ehrenstein Henrik Støvring Tobias Gaster Christine Marie Eggertsen |
| author_facet | Irene Petersen Vera Ehrenstein Henrik Støvring Tobias Gaster Christine Marie Eggertsen |
| author_sort | Irene Petersen |
| collection | DOAJ |
| description | The E value method deals with unmeasured confounding, a key source of bias in observational studies. The E value method is described and its use is shown in a worked example of a meta-analysis examining the association between the use of antidepressants in pregnancy and the risk of miscarriage. |
| format | Article |
| id | doaj-art-ec410601d2de4ed7a0d02ec8d9733e18 |
| institution | OA Journals |
| issn | 2754-0413 |
| language | English |
| publishDate | 2023-10-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Medicine |
| spelling | doaj-art-ec410601d2de4ed7a0d02ec8d9733e182025-08-20T02:30:35ZengBMJ Publishing GroupBMJ Medicine2754-04132023-10-012110.1136/bmjmed-2022-000366Quantifying the impact of unmeasured confounding in observational studies with the E valueIrene Petersen0Vera Ehrenstein1Henrik Støvring2Tobias Gaster3Christine Marie Eggertsen43 Department of Clinical Epidemiology, Aarhus University & Aarhus University Hospital, Aarhus, Denmark3 Department of Clinical Epidemiology, Aarhus University & Aarhus University Hospital, Aarhus, DenmarkSteno Diabetes Centre Aarhus, Aarhus, DenmarkAarhus University, Aarhus, DenmarkAarhus University, Aarhus, DenmarkThe E value method deals with unmeasured confounding, a key source of bias in observational studies. The E value method is described and its use is shown in a worked example of a meta-analysis examining the association between the use of antidepressants in pregnancy and the risk of miscarriage.https://bmjmedicine.bmj.com/content/2/1/e000366.full |
| spellingShingle | Irene Petersen Vera Ehrenstein Henrik Støvring Tobias Gaster Christine Marie Eggertsen Quantifying the impact of unmeasured confounding in observational studies with the E value BMJ Medicine |
| title | Quantifying the impact of unmeasured confounding in observational studies with the E value |
| title_full | Quantifying the impact of unmeasured confounding in observational studies with the E value |
| title_fullStr | Quantifying the impact of unmeasured confounding in observational studies with the E value |
| title_full_unstemmed | Quantifying the impact of unmeasured confounding in observational studies with the E value |
| title_short | Quantifying the impact of unmeasured confounding in observational studies with the E value |
| title_sort | quantifying the impact of unmeasured confounding in observational studies with the e value |
| url | https://bmjmedicine.bmj.com/content/2/1/e000366.full |
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