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In this paper, we propose a parametric accelerated failure time (AFT) hazard-based regression model with the extended alpha-power exponential (EAPE) baseline distribution. The proposed model is called the extended alpha-power exponential-AFT (EAPE-AFT) regression model. We show that the EAPE distribution is closed under the AFT model. The parameters of the proposed EAPE-AFT model have been estimated by using the method of maximum likelihood estimation. An extensive simulation study was also conducted to examine the performance of the estimates under several scenarios based on the shapes of the baseline hazard function. Finally, real-life censored survival data has been used to illustrate the applicability of the proposed model. [ABSTRACT FROM AUTHOR]

In this paper, we propose a flexible family called the exponentiated alpha-power-G (EAP-G) family. The benefits of the proposed family include its analytical simplicity and its ability to confer flexibility to the baseline distributions in survival analysis. Based on the proposed approach, a three-parameter extension of the exponential distribution called the exponentiated alpha-power exponential (EAPE) distribution is studied in detail. Maximum likelihood is used to estimate the EAPE parameters, and its performance is evaluated via a simulation study. Furthermore, two real-world survival data are used to demonstrate the applicability and examine the flexibility of the proposed distribution. The EAPE distribution is compared to other competing generalizations of the exponential distribution. The real data analysis shows that the proposed model performed better among the competitors and could potentially be very adequate in describing and modeling a wide range of survival data. [ABSTRACT FROM AUTHOR]