Non-mixture Cure Fraction Model in the Presence of Right Censored Survival Data and Covariates Based on Nadarajah-Haghighi Distribution with Applications to Medical Data
Keywords:
Nadarajah-Haghighi distribution, long-term non-mixture model, censoring and Colorectal cancerAbstract
In survival analysis it is assumed that every individual in the study population will eventually experience the event of interest if followed-up for a long period of time. However, there are some occasions in which a proportion of the population will never experience the event of interest. Hence, cure fraction models are used in modelling such type of data. The present paper introduces the Nadarajah-Haghighi distribution in the presence of cure fraction, right censored data and covariates. Comprehensive statistical properties of the model were explored. Inferences for the proposed model were obtained under the maximum likelihood and Bayesian approaches. Simulation study was provided in order to ascertain the performance of the maximum likelihood estimates. Illustrations of the proposed methodology were made by considering medical data sets using maximum likelihood and Bayesian methods. Results of the applications showed that the proposed methodology is a good competitor.
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