1
Master's student at the University of Sistan and Baluchestan
2
Faculty member of Sistan and Baluchestan University
3
Faculty member of the Faculty of Basic Sciences and Engineering, Bijar
Abstract
Large populations often face the problem of heterogeneity in survival analysis. Individuals are flexible in how they deal with the cause of death, respond to treatment, and are affected by risk factors. Ignoring this heterogeneity can lead to incorrect results. To overcome these problems, we introduce the unstable proportional hazard rate model. In this article, we introduce the unstable proportional hazard rate model and study its features. We examine the fitting of the unstable model to right-censored data in the presence of explanatory variables (observable variables). In the form of a practical example for fitting the unstable model to data, considering the Weibull basic distribution and exponential in the likelihood functions, they are used to estimate the model parameters and compare the models with different criteria.
Melanouri, M., Naderi, H., Ahmadzadeh, H. & Izadkhah, S. (2020). Using the Proportional Hazard Rate Unstable Model in Real Data Analysis. Andishe_ye Amari, 25(1), 25-31.
MLA
Melanouri, M., Naderi, H., Ahmadzadeh, H., & Izadkhah, S. "Using the Proportional Hazard Rate Unstable Model in Real Data Analysis", Andishe_ye Amari, 25, 1, 2020, 25-31.
HARVARD
Melanouri M., Naderi H., Ahmadzadeh H., Izadkhah S. (2020). 'Using the Proportional Hazard Rate Unstable Model in Real Data Analysis', Andishe_ye Amari, 25(1), pp. 25-31.
CHICAGO
M. Melanouri, H. Naderi, H. Ahmadzadeh & S. Izadkhah, "Using the Proportional Hazard Rate Unstable Model in Real Data Analysis," Andishe_ye Amari, 25 1 (2020): 25-31,
VANCOUVER
Melanouri M., Naderi H., Ahmadzadeh H., Izadkhah S. Using the Proportional Hazard Rate Unstable Model in Real Data Analysis. Andishe_ye Amari. 2020;25(1):25-31 (In Persian).
