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

Durga H. Kutal and Lianfen Qian
Additional contact information
Durga H. Kutal: Department of Mathematical Sciences, Florida Atlantic University, Boca Raton, FL 33431, USA
Lianfen Qian: Department of Mathematical Sciences, Florida Atlantic University, Boca Raton, FL 33431, USA

Stats, 2018, vol. 1, issue 1, 1-13

Abstract: 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 Fréchet susceptible distribution to evaluate the performance of the method. Compared with Weibull and exponentiated exponential distributions, the non-mixture Fréchet 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.

Keywords: Non-mixture model; Fréchet distribution; Right-censored survival data; Maximum likelihood method (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2571-905X/1/1/13/pdf (application/pdf)
https://www.mdpi.com/2571-905X/1/1/13/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jstats:v:1:y:2018:i:1:p:13-188:d:183187

Access Statistics for this article

Stats is currently edited by Mrs. Minnie Li

More articles in Stats from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().