Krahasoni metodat

	Studimi rast-kontroll me qasje Bajeziane	Studi i rast-kontroll me çiftim
Fusha	Epidemiologji	Epidemiologji
Familja	Process / pipeline	Process / pipeline
Viti i origjinës	1990s–2000s (systematic application); Bayesian inference foundations: Bayes/Laplace 18th–19th c.	1950s–1970s
Krijuesi	Sander Greenland (Bayesian epidemiology formalization); earlier Bayesian logistic methods: Leonard (1972)	Brian MacMahon and others; systematised by Schlesselman (1982)
Lloji	Observational analytic study with Bayesian inference	Observational analytic design
Burimi themelues	Greenland, S. (2006). Bayesian perspectives for epidemiological research: I. Foundations and basic methods. International Journal of Epidemiology, 35(3), 765-775.	Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755474
Emërtime të tjera	Bayesian case-control design, Bayesian odds ratio estimation, Bayesian matched case-control, Bayesian logistic regression case-control	matched case-referent study, individually matched case-control, pair-matched case-control, matched case-control design
Të lidhura	6	5
Përmbledhja	A Bayesian case-control study applies Bayesian statistical inference to the classic case-control epidemiological design, formally combining prior knowledge about exposure-disease associations with observed case and control data to estimate posterior odds ratios and credible intervals. Rather than relying solely on observed data, the Bayesian framework allows investigators to incorporate external evidence — from prior studies, expert knowledge, or mechanistic understanding — into the analysis, yielding probability statements about effect sizes that are often more interpretable than classical p-values and confidence intervals.	A matched case-control study is an observational epidemiological design in which each case (a person with the disease or outcome of interest) is paired with one or more controls (persons without the outcome) who share one or more characteristics — such as age, sex, or clinical setting — to control confounding. Exposure history is then compared between cases and their matched controls to estimate the odds ratio of the exposure-disease association.