A Non-Mixture Cure Model for Right-Censored Data with Frechet Distribution

被引：8
|
作者：
Kutal, Durga H. [1 ,2 ]
Qian, Lianfen [1 ,3 ]
机构：
[1] Florida Atlantic Univ, Dept Math Sci, Boca Raton, FL 33431 USA
[2] Wake Forest Univ, Winston Salem, NC 27101 USA
[3] Wenzhou Univ, Wenzhou, Peoples R China
来源：
STATS | 2018年 / 1卷 / 01期
关键词：
Non-mixture model; Frechet distribution; Right-censored survival data; Maximum likelihood method;
D O I：
10.3390/stats1010013
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
This paper considers a non-mixture cure model for right-censored data. It utilizes the maximum likelihood method to estimate model parameters in the non-mixture cure model. The simulation study is based on Frechet susceptible distribution to evaluate the performance of the method. Compared with Weibull and exponentiated exponential distributions, the non-mixture Frechet distribution is shown to be the best in modeling a real data on allogeneic marrow HLA-matched donors and ECOG phase III clinical trial e1684 data.
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页码：176 / 188
页数：13
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