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| 베이지안 코호트 연구× | 패널 연구× | |
|---|---|---|
| 분야 | 연구설계 | 연구설계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | Formalised in health research from the 1990s onward | 1970s-1980s (econometric formalization); earlier social survey use from 1940s |
| 창시자≠ | 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 |
| 유형 | Quantitative longitudinal observational design | Quantitative longitudinal observational design |
| 원전≠ | Ibrahim, J. G., & Chen, M. H. (2000). Power prior distributions for regression models. Statistical Science, 15(1), 46–60. DOI ↗ | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 |
| 별칭 | Bayesian cohort study, Bayesian prospective cohort, Bayesian longitudinal cohort analysis, Bayesian follow-up study | panel study, panel survey, longitudinal panel, repeated-measures panel |
| 관련≠ | 4 | 3 |
| 요약≠ | 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. |
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