Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Daudzcentru ligzdotā gadījumu-kontroles pētījuma× | Saskaņots ligzdots gadījuma-kontroles pētījums× | |
|---|---|---|
| Nozare | Epidemioloģija | Epidemioloģija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1990s–2000s (multicenter adaptation) | 1970s |
| Autors≠ | Nested case-control: Norman Mantel (1973); multicenter extension widely adopted in EPIC and other large consortium studies (1990s–2000s) | Mantel (1973), Thomas (1977); formalized by Breslow & Day (1980) |
| Tips≠ | Observational analytical study design | Observational analytic study design |
| Pirmavots≠ | 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 ↗ | Rothman, K.J., Greenland, S., & Lash, T.L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| Citi nosaukumi | multicenter NCC, multi-site nested case-control, pooled nested case-control, nested case-control within multicenter cohort | matched NCC study, nested case-control with matching, matched risk-set sampling, incidence density matched case-control |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | A multicenter nested case-control study embeds a case-control analysis within two or more geographically or institutionally distinct prospective cohorts. Cases who develop the outcome of interest are identified across all participating sites, then matched to controls sampled from the same risk sets, enabling pooled estimation of exposure-disease associations with greater statistical power and geographic generalizability than any single-center nested design. | A matched nested case-control study is an efficient observational design embedded within a defined cohort. When a participant develops the outcome of interest (a case), a small number of controls are sampled from those still at risk at that moment and matched to the case on key variables such as age, sex, or calendar time. This design preserves the temporal structure of the underlying cohort while sharply reducing the cost of exposure measurement. |
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