Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Аналіз виживаності з поправкою на ризик× | Зіставлення за показником схильності× | |
|---|---|---|
| Галузь≠ | Епідеміологія | Статистика досліджень |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 1972 (Cox regression); broader covariate-adjusted survival methods developed 1970s–1990s | 1983 |
| Автор методу≠ | D. R. Cox (regression framework); extensions via Kaplan & Meier, Breslow, and others | Paul Rosenbaum and Donald Rubin |
| Тип≠ | Observational and experimental analytical method | Method |
| Основоположне джерело≠ | Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society, Series B, 34(2), 187–220. 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≠ | covariate-adjusted survival analysis, adjusted time-to-event analysis, risk-stratified survival analysis, adjusted Kaplan-Meier / Cox analysis | PSM, propensity score weighting, covariate balance |
| Пов'язані≠ | 5 | 3 |
| Підсумок≠ | Risk-adjusted survival analysis estimates the time to an event of interest — such as death, relapse, or hospital readmission — while simultaneously accounting for baseline differences in patient characteristics (covariates). By incorporating confounders such as age, comorbidities, or disease severity, it produces hazard ratios, survival curves, and median survival estimates that are attributable to the factor of interest rather than to pre-existing risk differences between groups. | 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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