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Control Sampling Strategies for Case-Crossover Studies: An Assessment of Relative Efficiency
Abstract
The case-crossover study design is a method to assess the effect of transient exposures on the risk of onset of acute events. Control information for each case is based on his/her past exposure experience, and a self-matched analysis is conducted. Empiric evaluation of five approaches to the analysis of case-crossover data from a study of heavy physical exertion and acute myocardial infarction onset is shown. The data presented are from the Onset Study, a case-crossover study of the determinants of myocardial infarction onset conducted in 45 centers from August 1989 to October 1992. In model 1, exactly one control period (matched on clock-time) was sampled per case. In models 2-4, up to 25 control periods were sampled, and the effect of clock-time on the baseline hazard of infarction was modeled. In model 5, a census of the person-time experienced by each subject over the year preceding the infarction was sampled. The 95% confidence interval for model 1 was 2.7 times wider, and the relative efficiency, defined as v infinity/vM, where vM represents the asymptotic variance estimate of the estimated log relative risk with M control periods sampled per case, was only about 14% of model 5. In models 2-4, the efficiency increased with the number of control periods, regardless of the modeling assumptions. Even with many control periods sampled, models 2-4 achieved only half the efficiency of model 5. The control sampling strategy in any given case-crossover study should be selected with the trade-offs between precision and potential biases of the estimates in mind.
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“Because control information for each subject is based on his or her own past exposure experience, self-matching eliminates confounding by risk factors that are constant within individuals over the sampling period but often differ between study subjects.”
From Coffee and acute ischemic stroke onset: The Stroke Onset Study (2010) · cites this paper as [12]
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Metadata
- Authors
- Mittleman, M. A., Maclure, M., & Robins, J. M.
- Affiliations
- Harvard University (US)
- Corresponding author
- Mittleman, Murray A.
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 1995-07-01
- Volume
- 142
- Issue
- 1
- Pages
- 91-98
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- OpenAlex
- W2151672696
- Cited by
- 340
- References
- 0
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 8 · 2023: 10 · 2022: 11 · 2021: 8 · 2020: 4 · 2019: 10 · 2018: 12 · 2017: 14 · 2016: 13 · 2015: 21 · 2014: 23 · 2013: 13 · 2012: 15
- FWCI
- 10.32
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Heart, Lung, and Blood Institute (HL41016, R01HL041016)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Keywords
- case-crossover design, relative efficiency, acute myocardial infarction, transient exposure, asymptotic variance
- MeSH terms
- Adult, Aged, Aged, 80 and over, Female, Humans, Male, Middle Aged, Myocardial Infarction, Risk, Models, Statistical, Exercise, Bias, Confounding Factors, Epidemiologic, Case-Control Studies, Cross-Over Studies
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