This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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236
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Type:
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Contributed
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Date/Time:
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Monday, August 2, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #307240 |
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Title:
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A Joint Model of Longitudinal Data and Time-to-Event Data with Cure Fraction
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Author(s):
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Ashok Panneerselvam*+ and Mark Schluchter
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Companies:
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Case Western Reserve University and Case Western Reserve University
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Address:
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12000 Fairhill Road, Cleveland, OH, 44120, USA
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Keywords:
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Joint Model ;
Cure Fraction ;
EM Algorithm ;
Prostate Cancer ;
PSA
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Abstract:
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A joint model to analyze longitudinal prostate specific antigen (PSA) data and time to recurrence or metastasis in prostate cancer patients after receiving radiation therapy is developed. We assume a fraction of patients to be cured, i.e., where the risk of recurrence or metastasis is assumed to be zero. In the model, the probability of cure is modelled using a logit function, and the log transformed serial PSA measurements are modelled using a linear mixed effects model. In the uncured group the random effects of the longitudinal data and a suitable transformation of time to event is assumed to have a multivariate normal distribution. An EM algorithm is formulated to estimate the parameters of the model and the standard errors are obtained from bootstrapping. Properties of the model and estimates are examined using simulation studies.
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Authors who are presenting talks have a * after their name.
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