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Activity Number:
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53
- New Developments in Survival Analysis
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Type:
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Contributed
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Date/Time:
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Sunday, August 8, 2021 : 3:30 PM to 5:20 PM
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Sponsor:
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Biometrics Section
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Abstract #318228
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Title:
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Mixture and Non-Mixture Cure Models for Right-Censored Data with Modified Gompertz Distribution
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Author(s):
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Durga H Kutal* and Khyam N Paneru
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Companies:
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UW-Whitewater and The University of Tampa
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Keywords:
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Mixture;
Non-Mixture;
Cure Model;
Maximum Likelihood;
Modified Gompertz;
Right Censored
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Abstract:
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This project considers mixture and non-mixture cure models for right censored data. The maximum likelihood method used to estimate model parameters in the non-mixture cure model with modified Gompertz distribution. The simulation study is based on non-mixture cure model with modified Gompertz susceptible distribution to evaluate the performance of the method. The proposed model is applied to a real data set on allogeneic marrow HLA-matched donors and ECOG phase III clinical trial e1684. Moreover, we compared non-mixture and mixture cure models with modified Gompertz susceptible distribution using real data sets.
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Authors who are presenting talks have a * after their name.
