Linganisha mbinu

	Usajili wa Kuishi	Regressioni ya Kuishi ya Weibull ya Parametric
Nyanja	Takwimu	Uchanganuzi wa Uhai
Familia	Regression model	Survival analysis
Mwaka wa asili	1980s	1951
Mwanzilishi	Kalbfleisch & Prentice; Cox & Oakes	Waloddi Weibull
Aina	Parametric survival model	Fully parametric survival regression model
Chanzo asilia	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.
Majina mbadala	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
Zinazohusiana	3	4
Muhtasari	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.