Bandingkan metode

	Regresi kelangsungan hidup (Survival Regression)	Regresi Kelangsungan Hidup Parametrik Weibull
Bidang	Statistika	Analisis Survival
Keluarga	Regression model	Survival analysis
Tahun asal	1980s	1951
Pencetus	Kalbfleisch & Prentice; Cox & Oakes	Waloddi Weibull
Tipe	Parametric survival model	Fully parametric survival regression model
Sumber perintis	Kalbfleisch, J. D., & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. ISBN: 978-0471363576	Kalbfleisch, J. D. & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley.
Alias	accelerated failure time model, AFT model, parametric survival model, time-to-event regression	weibull aft model, weibull survival model, parametric survival regression, Weibull Regresyonu — Parametrik Hayatta Kalma
Terkait	3	4
Ringkasan	Survival regression models the time until an event occurs — such as death, failure, or relapse — as a function of covariates. Unlike ordinary regression, it properly accounts for censored observations (cases where the event had not yet occurred at the end of follow-up) by specifying a parametric distribution for the survival time and estimating covariate effects via maximum likelihood.	Weibull regression is a fully parametric survival model, formalised by Kalbfleisch and Prentice, that assumes survival times follow a Weibull distribution. A shape parameter controls whether the hazard increases, decreases, or remains constant over time, while covariates shift the scale of the distribution to express how predictors affect survival.