Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Когортное исследование× | Анализ выживаемости× | |
|---|---|---|
| Область≠ | Эпидемиология | Статистика исследований |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | Mid-20th century (formal epidemiological design codified ~1950s) | 1958 |
| Автор метода≠ | Doll & Hill (British Doctors Study, 1951); Snow (cholera, 1854) | Edward L. Kaplan and Paul Meier |
| Тип≠ | Observational longitudinal study design | Method |
| Основополагающий источник≠ | 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 ↗ |
| Другие названия≠ | longitudinal study, follow-up study, panel study, incidence study | Kaplan-Meier analysis, Cox regression, TTE analysis |
| Связанные≠ | 6 | 3 |
| Сводка≠ | 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. |
| ScholarGateНабор данных ↗ |
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