Salīdzināt metodes

	Saskaņotā Kaplan-Meier analīze	Kaplan-Meier analīze
Nozare	Epidemioloģija	Epidemioloģija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1958 (KM); matched application formalized 1980s–2000s	1958
Autors	Kaplan & Meier (KM method, 1958); matching extensions developed through propensity score methods (Rosenbaum & Rubin, 1983)	Edward L. Kaplan and Paul Meier
Tips	Nonparametric survival analysis with observational confounder control	Nonparametric survival estimator
Pirmavots	Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457-481.	Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481.
Citi nosaukumi	KM analysis in matched cohorts, propensity-matched survival curves, matched survival analysis, paired Kaplan-Meier	KM analysis, KM estimator, product-limit estimator, Kaplan-Meier curve
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.	Kaplan-Meier (KM) analysis is a nonparametric method for estimating the survival function from time-to-event data. Introduced by Kaplan and Meier in 1958, it produces the classic step-function survival curve that shows the probability of surviving beyond each observed event time, correctly accounting for censored observations — participants who left the study or had not yet experienced the event by the end of follow-up. It is one of the most widely used techniques in clinical and epidemiological research.