Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Байесовская оценка диагностического теста× | Анализ «доза-эффект»× | |
|---|---|---|
| Область | Эпидемиология | Эпидемиология |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1763 (theorem); clinical screening application formalized ~1959–1970s | Conceptual roots 16th century; modern epidemiological application mid-20th century |
| Автор метода≠ | Thomas Bayes (theorem, 1763); applied to clinical screening by Ledley & Lusted (1959) | Paracelsus (conceptual foundation); formalized by John Snow and later Bradford Hill |
| Тип≠ | Bayesian analytical framework for test evaluation | Quantitative analytical method |
| Основополагающий источник≠ | 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 |
| Другие названия | 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 |
| Связанные≠ | 6 | 4 |
| Сводка≠ | 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. |
| ScholarGateНабор данных ↗ |
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