Comparer des méthodes

	Modèle à inflation de zéros	Régression de survie
Domaine	Statistique	Statistique
Famille	Regression model	Regression model
Année d'origine	1992	1980s
Auteur d'origine	Diane Lambert	Kalbfleisch & Prentice; Cox & Oakes
Type	Count regression with excess zeros	Parametric survival model
Source fondatrice	Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1–14.	Kalbfleisch, J. D., & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. ISBN: 978-0471363576
Alias	ZIP model, ZINB model, zero-inflated Poisson, zero-inflated negative binomial	accelerated failure time model, AFT model, parametric survival model, time-to-event regression
Apparentées	6	3
Résumé	A zero-inflated model is a two-component mixture regression designed for count outcomes that contain more zero values than a standard Poisson or negative binomial distribution can accommodate. One component is a binary process that generates structural zeros; the other is a count process that generates both zeros and positive counts.	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.