Vertaile menetelmiä

	Bayesilainen eloonjäämisanalyysi	Bayesilainen regressio	Kaplan-Meierin selviytymisestimaattori
Tieteenala	Bayesilainen tilastotiede	Bayesilainen tilastotiede	Elinaika-analyysi
Menetelmäperhe	Bayesian methods	Bayesian methods	Survival analysis
Syntyvuosi	2001	—	1958
Kehittäjä	Ibrahim, Chen & Sinha	—	Kaplan, E. L. & Meier, P.
Tyyppi	Bayesian time-to-event model	Bayesian linear model	Non-parametric survival estimator
Alkuperäislähde	Ibrahim, J.G., Chen, M.-H. & Sinha, D. (2001). Bayesian Survival Analysis. Springer.	Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955	Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481.
Rinnakkaisnimet	bayesian sağkalım analizi, bayesian time-to-event analysis, bayesian hazard model	bayesian linear regression, probabilistic regression, bayesian regresyon	product-limit estimator, km curve, kaplan-meier sağkalım analizi
Liittyvät	4	2	2
Tiivistelmä	Bayesian survival analysis applies Bayesian inference to time-to-event models — Cox proportional hazards, parametric (Weibull, exponential), and cure models. Formalised comprehensively by Ibrahim, Chen and Sinha (2001), the approach encodes prior knowledge about hazard rates and regression coefficients, then updates it with censored survival data to yield posterior hazard ratios and credible intervals rather than single point estimates.	Bayesian regression is a probabilistic version of linear regression that treats the model parameters as uncertain quantities. Instead of returning a single best-fit estimate, it combines prior knowledge with the observed data to produce a full posterior probability distribution for each parameter, from which credible intervals and predictions are read off.	The Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups.