Salīdzināt metodes

	Saskaņotā Kaplan-Meier analīze	Matched Cohort Study
Nozare	Epidemioloģija	Epidemioloģija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1958 (KM); matched application formalized 1980s–2000s	Mid-20th century; propensity-score variant 1983
Autors	Kaplan & Meier (KM method, 1958); matching extensions developed through propensity score methods (Rosenbaum & Rubin, 1983)	Established practice; propensity-score matching formalized by Rosenbaum & Rubin (1983)
Tips	Nonparametric survival analysis with observational confounder control	Observational analytic study design
Pirmavots	Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457-481.	Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641
Citi nosaukumi	KM analysis in matched cohorts, propensity-matched survival curves, matched survival analysis, paired Kaplan-Meier	matched follow-up study, paired cohort study, propensity-matched cohort, matched prospective study
Saistītās	6	5
Kopsavilkums	Matched Kaplan-Meier analysis estimates and compares survival functions in groups that have been pre-balanced through individual or propensity-score matching. By applying the Kaplan-Meier product-limit estimator to matched cohorts or matched pairs, investigators can visualize time-to-event outcomes while controlling for confounders that would otherwise distort treatment or exposure comparisons in observational data.	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.