Vertaile menetelmiä

	Bayesiläinen seulontatestien arviointi	Dose-Response Analysis
Tieteenala	Epidemiologia	Epidemiologia
Menetelmäperhe	Process / pipeline	Process / pipeline
Syntyvuosi	1763 (theorem); clinical screening application formalized ~1959–1970s	Conceptual roots 16th century; modern epidemiological application mid-20th century
Kehittäjä	Thomas Bayes (theorem, 1763); applied to clinical screening by Ledley & Lusted (1959)	Paracelsus (conceptual foundation); formalized by John Snow and later Bradford Hill
Tyyppi	Bayesian analytical framework for test evaluation	Quantitative analytical method
Alkuperäislähde	Fletcher, R. H., Fletcher, S. W., & Fletcher, G. S. (2014). Clinical Epidemiology: The Essentials (5th ed.). Lippincott Williams & Wilkins. ISBN: 978-1451144475	Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641
Rinnakkaisnimet	Bayesian diagnostic test evaluation, Bayesian predictive value analysis, posterior predictive value approach, Bayes theorem screening	exposure-response analysis, concentration-response modeling, dose-response modeling, DRA
Liittyvät	6	4
Tiivistelmä	Bayesian screening test evaluation applies Bayes' theorem to quantify how a screening test result changes the probability that an individual truly has a disease. Rather than reporting sensitivity and specificity in isolation, the approach centres on predictive values — the probability of disease given a positive or negative test — which depend critically on disease prevalence in the population being screened. The framework allows systematic updating of pre-test probability to post-test probability and supports decision-making under uncertainty.	Dose-response analysis quantifies the relationship between the magnitude of an exposure (the dose) and the probability or rate of an outcome (the response). It is a core analytical strategy in epidemiology and toxicology, providing evidence that increasing exposure systematically increases — or decreases — the risk of disease. A demonstrated dose-response gradient is one of Bradford Hill's classic criteria supporting causal inference.