Exchangeability in the case-crossover design.
In cohort and case-control studies, confounding that arises as a result of differences in the distribution of determinants of the outcome between exposure groups leading to non-exchangeability are addressed by restriction, matching or with statistical models. In case-only studies, this issue is addressed by comparing each individual with his/herself. Although case-only designs use self-matching and only include individuals who develop the outcome of interest, issues of non-exchangeability are identical to those that arise in traditional case-control and cohort studies. In this review, we describe one type of case-only design, the case-crossover design, and discuss how the concept of exchangeability can be used to understand issues of confounding, carryover effects, period effects and selection bias in case-crossover studies.
Cardiovascular Epidemiology Research Unit, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA and Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA Cardiovascular Epidemiology Research Unit, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA and Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA mmittlem@bidmc.harvard.edu.
Murray A
MA
Mittleman
Cardiovascular Epidemiology Research Unit, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA and Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA Cardiovascular Epidemiology Research Unit, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA and Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA.
Elizabeth
E
Mostofsky
D016022:Case-Control Studies; D015331:Cohort Studies; D015986:Confounding Factors, Epidemiologic; D018592:Cross-Over Studies; D006801:Humans; D012107:Research Design; D015983:Selection Bias
Epidemiology; case-crossover