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Mixture models in survival analysis: Are they worth the risk?
Author(s) -
Farewell Ver T.
Publication year - 1986
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.2307/3314804
Subject(s) - inference , econometrics , survival analysis , event (particle physics) , fraction (chemistry) , disease , survival function , statistics , medicine , mathematics , computer science , artificial intelligence , physics , chemistry , organic chemistry , quantum mechanics
There has been a recurring interest in models for survival data which hypothesize subpopulations of individuals highly susceptible to some type of adverse event. Other individuals are assumed to be at much less risk. Most commonly, in clinical trials, these models attempt to estimate the fraction of patients cured of disease. The use of such models is examined, and the likelihood function is advocated as an informative inference tool.