ArticleAmerican journal of epidemiology2011
Potential for bias in case-crossover studies with shared exposures analyzed using SAS.
Article in American journal of epidemiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Acute Health Effects of Wildfire Smoke Exposure During a Compound Event: A Case-Crossover Study of the 2016 Great Smoky Mountain Wildfires.GeoHealth · 2023Article
- Night and evening shifts and risk of calling in sick within the next two days - a case-crossover study design based on day-to-day payroll data.Scandinavian journal of work, environment & health · 2023Article
- Air Quality Index and Emergency Department Visits and Hospitalizations for Childhood Asthma.Annals of the American Thoracic Society · 2022Article
- Optimising the case-crossover design for use in shared exposure settings.Epidemiology and infection · 2020Article
- Contribution of Satellite-Derived Aerosol Optical Depth PMAtmosphere · 2020Article
- Fine Particulate Matter and Respiratory Healthcare Encounters among Survivors of Childhood Cancers.International journal of environmental research and public health · 2019Article
- A comparison of estimators from self-controlled case series, case-crossover design, and sequence symmetry analysis for pharmacoepidemiological studies.BMC medical research methodology · 2018Article
- Article
- Methods to control for unmeasured confounding in pharmacoepidemiology: an overview.International journal of clinical pharmacy · 2016Review
- Is there a Hispanic Health Paradox in Sensitivity to Air Pollution? Hospital Admissions for Asthma, Chronic Obstructive Pulmonary Disease and Congestive Heart Failure Associated with NOAtmospheric environment (Oxford, England : 1994) · 2015Article
- Emergency department visits for asthma in relation to the Air Quality Health Index: a case-crossover study in Windsor, Canada.Canadian journal of public health = Revue canadienne de sante publique · 2014Article
- Heat waves and health outcomes in Alabama (USA): the importance of heat wave definition.Environmental health perspectives · 2014Article
- A mixed method to evaluate burden of malaria due to flooding and waterlogging in Mengcheng County, China: a case study.PloS one · 2014Article
- Ambient Sulphur Dioxide and Female ED Visits for Migraine.ISRN neurology · 2012Article
- Short-term exposure to ambient ozone and stroke hospital admission: A case-crossover analysis.Journal of exposure science & environmental epidemiologyArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The case-crossover method is an efficient study design for evaluating associations between transient exposures and the onset of acute events. In one common implementation of this design, odds ratios are estimated using conditional logistic or stratified Cox proportional hazards models, with data stratified on each individual event. In environmental epidemiology, where aggregate time-series data are often used, combining strata with identical exposure histories may be computationally convenient. However, when the SAS software package (SAS Institute Inc., Cary, North Carolina) is used for analysis, users can obtain biased results if care is not taken to properly account for multiple cases observed at the same time. The authors show that fitting a stratified Cox model with the "Breslow" option for handling tied failure times (i.e., ties = Breslow) provides unbiased health-effects estimates in case-crossover studies with shared exposures. The authors' simulations showed that using conditional logistic regression-or equivalently a stratified Cox model with the "ties = discrete" option-in this setting leads to health-effect estimates which can be biased away from the null hypothesis of no association by 22%-39%, even for small simulated relative risks. All methods tested by the authors yielded unbiased results under a simulated scenario with a relative risk of 1.0. This potential bias does not arise in R (R Foundation for Statistical Computing, Vienna, Austria) or Stata (Stata Corporation, College Station, Texas).
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