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Modelling Survival Data to Examine Length of Treatment Effectiveness in a Clinical Trial
Author(s) -
Slymen Donald J.
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.4710300803
Subject(s) - parametric statistics , statistics , clinical trial , survival analysis , hazard , hazard ratio , data set , proportional hazards model , treatment effect , econometrics , medicine , set (abstract data type) , parametric model , mathematics , computer science , confidence interval , chemistry , organic chemistry , programming language , traditional medicine
In some clinical trials where the experimental treatment is found to be effective in increasing survival, an important question is how long should the patient remain under treatment. Although the trial may not be designed to specifically answer this question, comparisons of the hazard curves among the treatment groups can yield some useful information. The survival data may be modelled using a flexible set of hazard functions and specific models are then chosen for further examination. This paper illustrates the approach using data from the Beta‐Blocker Heart Attack Trial. Parametric and semi‐parametric models are fitted and likelihood methods are used to assess length of treatment effectiveness.