Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| Kohorttitutkimus, jossa on täsmäytys (Matched Cohort Study)× | Propensity Score Matching× | |
|---|---|---|
| Tieteenala≠ | Epidemiologia | Tutkimuksen tilastomenetelmät |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | Mid-20th century; propensity-score variant 1983 | 1983 |
| Kehittäjä≠ | Established practice; propensity-score matching formalized by Rosenbaum & Rubin (1983) | Paul Rosenbaum and Donald Rubin |
| Tyyppi≠ | Observational analytic study design | Method |
| Alkuperäislähde≠ | 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 ↗ |
| Rinnakkaisnimet≠ | matched follow-up study, paired cohort study, propensity-matched cohort, matched prospective study | PSM, propensity score weighting, covariate balance |
| Liittyvät≠ | 5 | 3 |
| Tiivistelmä≠ | A matched cohort study is an observational design in which each exposed participant is paired with one or more unexposed counterparts who share key characteristics — such as age, sex, or comorbidity status — before both groups are followed forward in time to compare incident outcomes. Matching controls for measured confounders at the design stage, reducing bias that would otherwise require statistical adjustment alone. | 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. |
| ScholarGateAineisto ↗ |
|
|