Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Adjusting effect estimates for unmeasured confounding with validation data using propensity score calibration.

Til Stürmer1, Sebastian Schneeweiss, Jerry Avorn

  • 1Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02120, USA. til.sturmer@post.harvard.edu

American Journal of Epidemiology
|July 1, 2005
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Products That Pose Health Risks - Can Litigation Protect Us When Government Fails?

The New England journal of medicine·2026
Same author

Patterns of antithrombotic treatment after left atrial appendage occlusion.

Heart rhythm·2026
Same author

Out-of-Pocket Spending for Insulin by Medicare Beneficiaries After Monthly Caps.

JAMA internal medicine·2026
Same author

Fluticasone- vs Budesonide-Based Dual Therapy for COPD.

JAMA network open·2026
Same author

List Price Reductions Among Brand-Name ICS-LABA Inhalers In 2024 Were Associated With Increased Generic Uptake.

Health affairs (Project Hope)·2026
Same author

Risk of neutropenia-related hospitalisation among clozapine initiators.

BMJ mental health·2026

Propensity score calibration (PSC) is a new method to address unmeasured confounding in cohort studies using validation data. This sensitivity analysis for nonsteroidal anti-inflammatory drug (NSAID) use and mortality yielded more plausible results than traditional methods.

Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • Cohort studies often lack data on crucial confounders, complicating causal inference.
  • Existing sensitivity analyses for unmeasured confounding have limitations, particularly with multiple confounders.

Purpose of the Study:

  • To introduce and evaluate Propensity Score Calibration (PSC), a novel method to adjust for unmeasured confounding in cohort studies using validation data.
  • To assess the association between nonsteroidal anti-inflammatory drug (NSAID) use and 1-year mortality in elderly individuals using PSC.

Main Methods:

  • Controlled for measured confounding using propensity scores (PS) in the main cohort.
  • Estimated an "error-prone" PS (main cohort data) and a "gold standard" PS (including validation data) in a separate validation study.
  • Applied regression calibration to adjust regression coefficients based on the two PS estimates, termed Propensity Score Calibration (PSC).

Related Experiment Videos

Main Results:

  • Traditional adjustment for confounding yielded a hazard ratio of 0.80 (95% CI: 0.77, 0.83) for NSAID users.
  • Unadjusted analysis showed a hazard ratio of 0.68 (95% CI: 0.66, 0.71).
  • PSC analysis resulted in a hazard ratio of 1.06 (95% CI: 1.00, 1.12), suggesting a more plausible association.

Conclusions:

  • Propensity Score Calibration (PSC) offers a method to adjust for unmeasured confounding in cohort studies when validation data are available.
  • The PSC method produced a more plausible hazard ratio for NSAID use and mortality compared to traditional methods.
  • PSC should be considered a sensitivity analysis until its validity and limitations are further established across diverse settings.