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.

Detalles Bibliográficos
Autores principales: Gaster, Tobias, Eggertsen, Christine Marie, Støvring, Henrik, Ehrenstein, Vera, Petersen, Irene
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163534/
https://www.ncbi.nlm.nih.gov/pubmed/37159620
http://dx.doi.org/10.1136/bmjmed-2022-000366
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author Gaster, Tobias
Eggertsen, Christine Marie
Støvring, Henrik
Ehrenstein, Vera
Petersen, Irene
author_facet Gaster, Tobias
Eggertsen, Christine Marie
Støvring, Henrik
Ehrenstein, Vera
Petersen, Irene
author_sort Gaster, Tobias
collection PubMed
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.
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spelling pubmed-101635342023-05-07 Quantifying the impact of unmeasured confounding in observational studies with the E value Gaster, Tobias Eggertsen, Christine Marie Støvring, Henrik Ehrenstein, Vera Petersen, Irene BMJ Med Research 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. BMJ Publishing Group 2023-05-04 /pmc/articles/PMC10163534/ /pubmed/37159620 http://dx.doi.org/10.1136/bmjmed-2022-000366 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Research
Gaster, Tobias
Eggertsen, Christine Marie
Støvring, Henrik
Ehrenstein, Vera
Petersen, Irene
Quantifying the impact of unmeasured confounding in observational studies with the E value
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
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163534/
https://www.ncbi.nlm.nih.gov/pubmed/37159620
http://dx.doi.org/10.1136/bmjmed-2022-000366
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