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Ideas and Opinions |

Randomized Trials Analyzed as Observational Studies

Miguel A. Hernán, MD; Sonia Hernández-Díaz, MD; and James M. Robins, MD
[+] Article and Author Information

This article was published online first at www.annals.org on 10 September 2013.


From Harvard School of Public Health, Boston, Massachusetts.

Grant Support: In part by grants R01 HL080644 and R01 AI102634 from the National Institutes of Health.

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M13-1455.

Requests for Single Reprints: Miguel A. Hernán, MD, Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115; e-mail, miguel_hernan@post.harvard.edu.

Current Author Addresses: Drs. Hernán, Hernández-Diaz, and Robins: Harvard School of Public Health, Department of Epidemiology, 677 Huntington Avenue, Boston, MA 02115.

Author Contributions: Conception and design: M.A. Hernán, S. Hernández-Díaz, J.M. Robins.

Drafting of the article: M.A. Hernán, S. Hernández-Díaz, J.M. Robins.

Critical revision for important intellectual content: M.A. Hernán, S. Hernández-Diaz, J.M. Robins.

Final approval of the article: M.A. Hernán, S. Hernández-Diaz, J.M. Robins.

Statistical expertise: M.A. Hernán, S. Hernández-Díaz, J.M. Robins.

Obtaining of funding: M.A. Hernán.

Administrative, technical, or logistic support: M.A. Hernán.


Ann Intern Med. 2013;159(8): 560-562. doi:10.7326/0003-4819-159-8-201310150-00709
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Randomized trials are not always free of confounding and selection bias. This commentary posits that randomized trials with long follow-up are similar to observational studies and that “intention-to-treat” analysis of such studies may be inadequate. The authors propose use of g-methods to adjust for postrandomization confounding and selection bias.

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