Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Ризик-скориговане гніздове дослідження випадок-контроль× | Зіставлення за показником схильності× | |
|---|---|---|
| Галузь≠ | Епідеміологія | Статистика досліджень |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 1977 (nested case-control); risk-adjusted extensions 1980s–2000s | 1983 |
| Автор методу≠ | Thomas (1977) for nested case-control; risk adjustment extensions developed through pharmacoepidemiology literature (1980s–2000s) | Paul Rosenbaum and Donald Rubin |
| Тип≠ | Observational analytical study design | Method |
| Основоположне джерело≠ | 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 ↗ | 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 ↗ |
| Інші назви≠ | risk-adjusted NCC, covariate-adjusted nested case-control, propensity-score nested case-control, nested case-control with risk adjustment | PSM, propensity score weighting, covariate balance |
| Пов'язані≠ | 4 | 3 |
| Підсумок≠ | A risk-adjusted nested case-control study embeds a case-control comparison inside a defined cohort and explicitly accounts for differences in baseline risk between cases and controls through covariate adjustment — most commonly via risk scores, propensity scores, or stratification. It preserves the efficiency advantages of the nested design while reducing confounding attributable to pre-existing risk differentials, making it especially valuable in pharmacoepidemiology and clinical effectiveness research. | 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. |
| ScholarGateНабір даних ↗ |
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