Avoidable flaws in observational analyses: an application to statins and cancer

2019/10/01 by Barbra A. Dickerman, Xabier García-Albéniz, Xabier García‐Albéniz +4 · 1 voice · 1 citation
Biochemistry, Genetics and Molecular Biology · Mathematics · Medicine · #Advanced Causal Inference Techniques #Cancer, Lipids, and Metabolism #Lipoproteins and Cardiovascular Health

paper · doi:10.1038/s41591-019-0597-x

crossref issued 2019/10/01 · crossref published 2019/10/01 · crossref published-print 2019/10/01 · openalex publication_date 2019/10/01 · crossref published-online 2019/10/07 · crossref created 2019/10/07 · crossref deposited 2023/05/20 · openalex created_date 2025/10/10 · crossref indexed 2026/07/29 · openalex updated_date 2026/08/01

Citations

• Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available: Table 1.
• Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses

Cited by

• The Target Trial Framework for Causal Inference From Observational Data: Why and When Is It Helpful?

Discussions

• The important point is the alignment of eligibility and treatment assignment with time zero of follow-up (baseline)! Wonderful study (doi.org/10.1038/s415...) showed that is can strongly bias the resu [bsky, 0 points, 1 comments]