方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 队列研究× | 生存分析× | |
|---|---|---|
| 领域≠ | 流行病学 | 研究统计学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | Mid-20th century (formal epidemiological design codified ~1950s) | 1958 |
| 提出者≠ | Doll & Hill (British Doctors Study, 1951); Snow (cholera, 1854) | Edward L. Kaplan and Paul Meier |
| 类型≠ | Observational longitudinal study design | Method |
| 开创性文献≠ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 | Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| 别名≠ | longitudinal study, follow-up study, panel study, incidence study | Kaplan-Meier analysis, Cox regression, TTE analysis |
| 相关≠ | 6 | 3 |
| 摘要≠ | A cohort study assembles a group of individuals who share a common starting point — typically freedom from the outcome of interest — and follows them over time to observe who develops the outcome. By comparing incidence rates between exposed and unexposed subgroups, researchers can estimate relative risk and absolute risk differences. Cohort studies are the gold-standard observational design for measuring disease incidence and establishing temporal relationships between exposure and outcome. | Survival analysis is a collection of statistical methods for modeling time from a defined starting point until an event of interest occurs (disease, recovery, death, equipment failure). Kaplan and Meier's nonparametric estimator (1958) and David Cox's proportional hazards model (1972) jointly enabled analysis of censored data—individuals whose event times are unknown because they left the study or were still event-free at follow-up. Indispensable in oncology, cardiology, infectious disease research, engineering reliability, and any field where time-to-event matters. |
| ScholarGate数据集 ↗ |
|
|