Сравнение методов

	Байесовские когортные исследования	Панельное исследование
Область	Дизайн исследования	Дизайн исследования
Семейство	Process / pipeline	Process / pipeline
Год появления	Formalised in health research from the 1990s onward	1970s-1980s (econometric formalization); earlier social survey use from 1940s
Автор метода	Synthesis of cohort epidemiology (Doll & Hill, 1950s) with Bayesian inference (Bayes, Laplace, Jeffreys)	Social science and econometric traditions; systematized by Cheng Hsiao and others from the 1970s-1980s
Тип	Quantitative longitudinal observational design	Quantitative longitudinal observational design
Основополагающий источник	Ibrahim, J. G., & Chen, M. H. (2000). Power prior distributions for regression models. Statistical Science, 15(1), 46–60.	Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717
Другие названия	Bayesian cohort study, Bayesian prospective cohort, Bayesian longitudinal cohort analysis, Bayesian follow-up study	panel study, panel survey, longitudinal panel, repeated-measures panel
Связанные	4	3
Сводка	Bayesian cohort research follows a defined group of individuals over time to track outcomes, and uses Bayesian statistical inference to update beliefs about risk, incidence, or causal effects as follow-up data accumulate. Prior knowledge — from earlier studies, registries, or expert judgment — is formalised into a prior distribution and combined with the cohort's likelihood to yield a posterior distribution that quantifies uncertainty in a directly interpretable way.	Panel research is a quantitative longitudinal design in which the same individuals, organizations, or other units are measured repeatedly across two or more time points. Unlike cross-sectional surveys that capture a single snapshot, a panel tracks change within units, enabling researchers to separate genuine within-unit change from between-unit differences and to model causal dynamics over time.