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

Autor: Lianfen Qian, Durga H. Kutal
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Popis: 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. Comparing 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.
Databáze: OpenAIRE