A New Cure Rate Model Based on Flory–Schulz Distribution: Application to the Cancer Data

Abstract

In this article a new flexible survival cure rate model is introduced by assuming that the number of competing causes of the event of interest follows the Flory–Schulz distribution and the competing causes follow the generalized truncated Nadarajah–Haghighi distribution. Parameter estimation for the proposed model is derived based on the maximum likelihood estimation method. A simulation study is performed to show the performance of the ML estimators. We discuss three real data applications related to real cancer data sets to assess the usefulness of the proposed model compared with some existing cure rate models for the sake of comparison.

Keywords

• cure rate model
• Flory–Schulz distribution
• generalized truncated Nadarajah–Haghighi distribution
• cancer data
• maximum likelihood estimation