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Abstract Details
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Activity Number:
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412
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Consulting
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| Abstract - #300758 |
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Title:
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Survival Analysis and Model Comparisons for a Breast Cancer Data Set
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Author(s):
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Hong Li*+
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Companies:
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Cameron University
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Address:
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, Lawton, OK, 73505,
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Keywords:
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Proportional hazards model ;
survival function ;
hazard function ;
log-likelihood
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Abstract:
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A survival analysis on a data set of 295 early breast cancer patients from the Netherlands Cancer Institute is performed in this paper. We assume a proportional hazards model, and select two sets of risk factors for death and metastasis for breast cancer patients respectively by using standard variable selection methods. In addition, a newly developed probability distribution-hypertabastic distribution and the hypertabastic proportional hazards model are introduced. To evaluate the performance of the new model and compare it with other popular distributions, we fit the Cox, Weibull and log-logistic models, in addition to the hypertabastic model. The results from the model comparisons show that the hypertabastic proportional hazards model outperforms all the comparison models when fitted to the breast cancer data. It indicates that it can be a flexible and promising alt
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Authors who are presenting talks have a * after their name.
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