A formal causal interpretation of the case-crossover design.
case-crossover
causal inference
counterfactual framework
Journal
Biometrics
ISSN: 1541-0420
Titre abrégé: Biometrics
Pays: United States
ID NLM: 0370625
Informations de publication
Date de publication:
06 2023
06 2023
Historique:
received:
01
05
2020
accepted:
08
12
2021
medline:
21
6
2023
pubmed:
25
8
2022
entrez:
24
8
2022
Statut:
ppublish
Résumé
The case-crossover design of Maclure is widely used in epidemiology and other fields to study causal effects of transient treatments on acute outcomes. However, its validity and causal interpretation have only been justified under informal conditions. Here, we place the design in a formal counterfactual framework for the first time. Doing so helps to clarify its assumptions and interpretation. In particular, when the treatment effect is nonnull, we identify a previously unnoticed bias arising from strong common causes of the outcome at different person-times. We analyze this bias and demonstrate its potential importance with simulations. We also use our derivation of the limit of the case-crossover estimator to analyze its sensitivity to treatment effect heterogeneity, a violation of one of the informal criteria for validity. The upshot of this work for practitioners is that, while the case-crossover design can be useful for testing the causal null hypothesis in the presence of baseline confounders, extra caution is warranted when using the case-crossover design for point estimation of causal effects.
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
1330-1343Subventions
Organisme : NIH HHS
ID : R37 AI102634
Pays : United States
Commentaires et corrections
Type : CommentIn
Type : CommentIn
Type : CommentIn
Type : CommentIn
Informations de copyright
© 2022 The Authors. Biometrics published by Wiley Periodicals LLC on behalf of International Biometric Society.
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