The exponentiated exponential mixture and non-mixture cure rate model in the presence of covariates.
This paper presents estimates for the parameters included in long-term mixture and non-mixture lifetime models, applied to analyze survival data when some individuals may never experience the event of interest. We consider the case where the lifetime data have a two-parameters exponentiated exponential distribution. The two-parameter exponentiated exponential or the generalized exponential distribution is a particular member of the exponentiated Weibull distribution introduced by [31]. Classical and Bayesian procedures are used to get point and confidence intervals of the unknown parameters. We consider a general survival model where the scale, shape and cured fraction parameters of the exponentiated exponential distribution depends on covariates.
Universidade Estadual de Maringá, Departamento de Estatística, DEs/UEM, Maringá, PR, Brazil. Electronic address: jmazucheli@uem.br.
Josmar
J
Mazucheli
Emílio A
EA
Coelho-Barros
Jorge Alberto
JA
Achcar
D000163:Acquired Immunodeficiency Syndrome / Q000517:prevention & control / Q000523:psychology; D001499:Bayes Theorem; D016208:Databases, Factual / Q000706:statistics & numerical data; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D012044:Regression Analysis; D012309:Risk-Taking; D019966:Substance-Related Disorders / Q000523:psychology / Q000628:therapy; D016019:Survival Analysis
Exponentiated Weibull distribution; Long-term data; Mixture lifetime model; Non-mixture lifetime model