Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Párová vnořená případově-kontrolní studie× | Párování na základě skóre propensity× | |
|---|---|---|
| Obor≠ | Epidemiologie | Statistika ve výzkumu |
| Rodina | Process / pipeline | Process / pipeline |
| Rok vzniku≠ | 1970s | 1983 |
| Tvůrce≠ | Mantel (1973), Thomas (1977); formalized by Breslow & Day (1980) | Paul Rosenbaum and Donald Rubin |
| Typ≠ | Observational analytic study design | Method |
| Původní zdroj≠ | Rothman, K.J., Greenland, S., & Lash, T.L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 | Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. DOI ↗ |
| Další názvy≠ | matched NCC study, nested case-control with matching, matched risk-set sampling, incidence density matched case-control | PSM, propensity score weighting, covariate balance |
| Příbuzné≠ | 5 | 3 |
| Shrnutí≠ | 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. | Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias. |
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