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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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BackgroundRelationship Between air Pollution and Daily Mortality in a Tropical City: Kaohsiung, Taiwan
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Albert, C. M., Rosenthal, L., Calkins, H., Steinberg, J. S., Ruskin, J. N., Wang, P., Muller, J. E., & Mittleman, M. A. (2007) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2007.06.059 · Cited by 61
Self-citationStatistical Methods for Naturalistic Driving Studies
Guo, F. (2018) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-030718-105153 · Cited by 59
Wade, T. J., Lin, C. J., Jagai, J. S., & Hilborn, E. D. (2014) · PLoS ONE · doi:10.1371/journal.pone.0110474 · Cited by 58
“We applied a fixed-effect conditional logistic regression model, standard for case-crossover studies [19,20,23], and shown to be unbiased when the time-stratified bi-directional case-crossover design is used for control selection [21,22].”
MethodYamauchi, T., Inagaki, M., Yonemoto, N., Iwasaki, M., Inoue, M., Akechi, T., Iso, H., Tsugane, S., & on behalf of the JPHC Study Group (2014) · Psycho-Oncology · doi:10.1002/pon.3529 · Cited by 56
“Furthermore, to adjust for unmeasured confounding factors, a case-crossover analysis [13,29,30] was performed for all patients with cancer who died by suicide or ECIs.”
MethodResultWithin‐subject exposure dependency in case‐crossover studies
Vines, S. K., & Farrington, P. (2001) · Statistics in Medicine · doi:10.1002/sim.960 · Cited by 57
Tsai, S., Chiu, H., Liou, S.-H., & Yang, C. (2014) · Journal of Toxicology and Environmental Health · doi:10.1080/15287394.2014.922388 · Cited by 55
“Data were analyzed using the casecrossover technique (Maclure, 1991; Marshall and Jackson, 1993; Mittleman et al., 1995).”
MethodGlove Use and the Relative Risk of Acute Hand Injury: A Case-Crossover Study
Sorock, G. S., Lombardi, D. A., Peng, D. K., Hauser, R. B., Eisen, E. A., Herrick, R. F., & Mittleman, M. A. (2004) · Journal of Occupational and Environmental Hygiene · doi:10.1080/15459620490424500 · Cited by 58
“The analysis of the case-crossover data for glove use as a risk factor was conducted using standard methods for stratified analyses.(15,16) In the case-crossover design the individual subject is the stratifying variable.”
MethodSelf-citationAlcohol and Acute Ischemic Stroke Onset
Mostofsky, E., Burger, M. R., Schlaug, G., Mukamal, K. J., Rosamond, W. D., & Mittleman, M. A. (2010) · Stroke · doi:10.1161/strokeaha.110.580092 · Cited by 58
“病例交叉研究中的每位患者形成了其各自独立 的分层,并进行自身对照 ([21,22])。所观察到的危险期”
Self-citationTriggering of acute myocardial infarction by different means of transportation
Peters, A., von Klot, S., Mittleman, M. A., Meisinger, C., Hörmann, A., Kuch, B., & Wichmann, H. ‐. (2012) · European Journal of Preventive Cardiology · doi:10.1177/2047487312446672 · Cited by 56
“Conditional logistic regression models were used to assess the association between transient individual level traffic exposures and AMI onset.(16) We computed odds ratios as a measure of relative risk (RR) of having an AMI during periods of time spent in traffic compared with time not spent in traffic within an indivi…”
MethodSelf-citationDesign issues in case-control studies
Wacholder, S. (1995) · Statistical Methods in Medical Research · doi:10.1177/096228029500400403 · Cited by 54
Episodic Alcohol Use and Risk of Nonfatal Injury
Borges, G. L. G. (2004) · American Journal of Epidemiology · doi:10.1093/aje/kwh073 · Cited by 54
“We report relative risk estimates for alcohol use within 6 hours prior to injury, using different time periods for control comparisons ( 19 ).”
MethodChen, Y.-C., Weng, Y., Chiu, Y.-W., & Yang, C. (2015) · Journal of Toxicology and Environmental Health · doi:10.1080/15287394.2015.1083520 · Cited by 53
“Data were analyzed using the casecrossover technique (Maclure 1991; Marshall and Jackson 1993; Mittleman et al. 1995).”
Method
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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