Võrdle meetodeid

	Bayesian Case-Crossover Design	Juhtum-ristkasuuringu disain
Valdkond	Epidemioloogia	Epidemioloogia
Perekond	Process / pipeline	Process / pipeline
Tekkeaasta	1991 (case-crossover); Bayesian extension ~2000s	1991
Looja	Malcolm Maclure (case-crossover); Bayesian extension developed by Lumley, Sheppard, and colleagues	Malcolm Maclure
Tüüp	Self-matched observational study design with Bayesian inference	Observational epidemiological study design
Algallikas	Maclure, M. (1991). The case-crossover design: a method for studying transient effects on the risk of acute events. American Journal of Epidemiology, 133(2), 144–153.	Maclure, M. (1991). The case-crossover design: A method for studying transient effects on the risk of acute events. American Journal of Epidemiology, 133(2), 144–153.
Rööpnimetused	Bayesian case-crossover, BCCO, Bayesian self-matched design, Bayesian within-person crossover	case-crossover study, CCO design, self-matched case study, within-person crossover case study
Seotud	2	3
Kokkuvõte	The Bayesian case-crossover design is a self-matched epidemiological method that estimates the transient effect of a time-varying exposure on the risk of an acute event. Each case serves as their own control, eliminating confounding by time-stable individual characteristics. Bayesian inference replaces or supplements the classical conditional logistic regression, enabling the incorporation of prior knowledge, more stable estimation in sparse data, and full uncertainty quantification via posterior distributions.	The case-crossover design is an observational epidemiological method that estimates whether a transient exposure triggers an acute event by comparing each case's exposure during a brief hazard window immediately before the event to their own exposure during earlier control periods. Because each person serves as their own control, all stable personal characteristics are automatically adjusted for, making the design especially powerful for studying intermittent exposures and sudden-onset outcomes such as myocardial infarction, stroke, or injury.