Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Вложенное случай-контроль исследование (nested case-control study)× | Анализ выживаемости× | |
|---|---|---|
| Область≠ | Эпидемиология | Статистика исследований |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1973–1977 | 1958 |
| Автор метода≠ | Nathan Mantel (1973); D. C. Thomas (1977 formalization) | Edward L. Kaplan and Paul Meier |
| Тип≠ | Hybrid observational study design | Method |
| Основополагающий источник≠ | Thomas, D. C. (1977). Addendum to: Methods of cohort analysis: Appraisal by application to asbestos mining. Journal of the Royal Statistical Society, Series A, 140(4), 469–491. link ↗ | Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| Другие названия≠ | NCC study, nested CC design, case-control within cohort, density sampling case-control | Kaplan-Meier analysis, Cox regression, TTE analysis |
| Связанные≠ | 6 | 3 |
| Сводка≠ | A nested case-control study is an efficient observational design embedded within a defined cohort. For each participant who develops the outcome of interest (a case), a small number of matched controls are sampled from those still at risk at the same point in time. This density-sampling strategy yields odds ratios that approximate incidence-rate ratios from the full cohort at a fraction of the data-collection cost — making it the preferred alternative when measuring exposures for all cohort members would be prohibitively expensive or technically demanding. | 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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