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On Generalized Log‐Logistic Model for Censored Survival Data
Author(s) -
Singh Karan P.,
Lee Carl M.S.,
George E. Olusegun
Publication year - 1988
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710300714
Subject(s) - log logistic distribution , logistic regression , statistics , weibull distribution , generalization , mathematics , parametric model , parametric statistics , hazard , proportional hazards model , econometrics , hazard ratio , confidence interval , probability distribution , mathematical analysis , distribution fitting , chemistry , organic chemistry
In the analysis of survival data with parametric models, it is well known that the Weibull model is not suitable for modeling cases where the hazard rate is non‐monotonic. For such cases, log‐logistic model is frequently used. However, due to the symmetric property of the log‐logistic model, it may be poor for the cases where the hazard rate is skewed or heavily tailed. In this paper, we suggest a generalization of the log‐logistic model by introducing a shape parameter. This generalized model is then applied to fit the lung cancer data of Prentice (1973). The results seem to improve over those obtained by using the log‐logistic model.