Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Retrospektīvā konkurējošo risku analīze× | Retrospektīvais kohortas pētījums× | |
|---|---|---|
| Nozare | Epidemioloģija | Epidemioloģija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1978 (cause-specific); 1999 (subdistribution/Fine-Gray) | Mid-20th century (widely formalized 1950s–1970s) |
| Autors≠ | Fine & Gray (subdistribution model); Prentice et al. (cause-specific framework) | Systematic use attributed to early 20th-century occupational epidemiology; formalized in modern epidemiological theory by Brian MacMahon and others |
| Tips≠ | Retrospective observational survival analysis | Observational analytic study |
| Pirmavots≠ | Fine, J. P., & Gray, R. J. (1999). A proportional hazards model for the subdistribution of a competing risk. Journal of the American Statistical Association, 94(446), 496–509. DOI ↗ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| Citi nosaukumi | retrospective CRA, competing risks survival analysis (retrospective), cause-specific hazard analysis (retrospective), subdistribution hazard analysis (retrospective) | historical cohort study, non-concurrent cohort study, retrospective follow-up study, historical prospective study |
| Saistītās≠ | 4 | 6 |
| Kopsavilkums≠ | Retrospective competing risks analysis applies competing risks methodology to historical (already-collected) time-to-event data in which subjects can experience one of several mutually exclusive endpoints. It uses the cumulative incidence function and cause-specific or subdistribution hazard models to estimate the probability of each event type while accounting for the fact that occurrence of one event permanently precludes the others. Widely used in oncology, cardiology, and transplant medicine where administrative or registry records are the data source. | A retrospective cohort study assembles a group of individuals who share a common starting point and reconstructs their exposure history and subsequent outcomes entirely from pre-existing records. Because the data have already been collected before the study begins, the design is far faster and cheaper than a prospective cohort; however, the researcher must work with whatever information was recorded at the time rather than collecting purpose-built measurements. |
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