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Activity Number:
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307
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Type:
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Contributed
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Date/Time:
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Wednesday, August 11, 2004 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #300491 |
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Title:
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On Semiparametric Transformation Cure Models
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Author(s):
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Wenbin Lu*+ and Zhiliang Ying
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Companies:
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North Carolina State University and Columbia University
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Address:
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2501 Founder's Dr., Raleigh, NC, 27695,
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Keywords:
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cure rate models ; estimating equations ; long-term survivors ; martingale ; transformation models
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Abstract:
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Survival models with a cure rate have received much attention in recent years. These models are useful when a proportion of study subjects never experience the event of interest. Such examples can be found in many disciplines, including biomedical sciences, economics, sociology, and engineering science. A general class of semiparametric transformation cure models will be studied for the analysis of survival data with long-term survivors. It combines a logistic regression for the probability of event occurrence with the class of transformation models for the time of occurrence. Included as special cases are the proportional hazards cure model and the proportional odds cure model. Estimating equations are proposed for parameter estimation. It is shown that the resulting estimators are asymptotically normal, with variance-covariance matrix that has a closed form and can be consistently estimated by the usual plug-in method. Simulation studies show that the proposed approach is appropriate for practical use. An application to data from a breast cancer study is given to illustrate the methodology.
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