পদ্ধতির তুলনা করুন

	বহুকেন্দ্রিক প্রতিযোগী ঝুঁকি বিশ্লেষণ	কপ্ল্যান-মেয়ার বিশ্লেষণ
ক্ষেত্র	মহামারীবিদ্যা	মহামারীবিদ্যা
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	1999 (Fine-Gray); extended to multicenter settings throughout 2000s–2010s	1958
প্রবর্তক	Fine & Gray (subdistribution hazard model); Prentice et al. (cause-specific hazard model)	Edward L. Kaplan and Paul Meier
ধরন	Survival / time-to-event statistical analysis	Nonparametric survival estimator
মৌলিক উৎস	Fine, J. P., & Gray, R. J. (1999). A proportional hazards model for the subdistribution of a competing risk. Journal of the American Statistical Association, 94(446), 496–509.	Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481.
অপর নাম	multicenter CRA, multi-site competing risks, multicenter cumulative incidence analysis, polycentric competing risks study	KM analysis, KM estimator, product-limit estimator, Kaplan-Meier curve
সম্পর্কিত	4	5
সারসংক্ষেপ	Multicenter competing risks analysis is a time-to-event method applied across multiple clinical centers to estimate the probability of a specific event of interest when other mutually exclusive events — competing risks — can preclude its occurrence. By pooling data from diverse sites, it achieves the sample sizes needed to model rare events and enables assessment of center-level variation in cumulative incidence and covariate effects.	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.