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All Journal African Multidisciplinary Journal of Sciences and Artificial Intelligence Kwaghe International Journal of Arts, Humanities and Religious Studies
Aliyu Yakubu
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Environmental Science Materials Science & Nanotechnology Social Sciences

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The Weibull-Exponentiated Exponential Cure Fraction Model for Right Censored Survival Data with Applications to Cancer Data Aliyu Yakubu; Naziru Isah Muhammad; Jamilu Yunusa Falgore; Adam Rabiu
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 1 No 2 (2024): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v1i2.3855

Abstract

The cure fraction model also known as the long-term survival model is used in fitting data from a population with two different types of individuals: individuals who experienced the event of interest (susceptible) and individuals who will never experience the event of interest (non-susceptible). The present paper introduced a cure fraction model considering the Weibull exponentiated exponential distribution that will be used in modeling such type of information. The parameters of the model were estimated via the maximum likelihood procedure (MLE) under the assumption of right censoring. Furthermore, the statistical properties of the model were studied comprehensively. Simulation studies and medical data sets were used to demonstrate the applicability of the proposed methodology. Bias and standard error were used as discrimination criteria in the simulation study while Akaike Information criteria (AIC), Bayesian Information Criteria (BIC), and Consistent Akaike Information criteria (CAIC) were used as discrimination criteria in real-life applications. Results from the applications showed that the Weibull exponentiated exponential non-mixture cure fraction model is a strong competitor.
The Weibull-Exponentiated Exponential Cure Fraction Model for Right Censored Survival Data with Applications to Cancer Data Aliyu Yakubu; Naziru Isah Muhammad; Jamilu Yunusa Falgore; Adam Rabiu
Kwaghe International Journal of Arts, Humanities and Religious Studies Vol 1 No 1 (2024): Kwaghe International Journal of Arts, Humanities and Religious Studies
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/kijahrs.v1i1.3821

Abstract

The cure fraction model also known as the long-term survival model is used in fitting data from a population with two different types of individuals: individuals who experienced the event of interest (susceptible) and individuals who will never experience the event of interest (non-susceptible). The present paper introduced a cure fraction model considering the Weibull exponentiated exponential distribution that will be used in modeling such type of information. The parameters of the model were estimated via the maximum likelihood procedure (MLE) under the assumption of right censoring. Furthermore, the statistical properties of the model were studied comprehensively. Simulation studies and medical data sets were used to demonstrate the applicability of the proposed methodology. Bias and standard error were used as discrimination criteria in the simulation study while Akaike Information criteria (AIC), Bayesian Information Criteria (BIC), and Consistent Akaike Information criteria (CAIC) were used as discrimination criteria in real-life applications. Results from the applications showed that the Weibull exponentiated exponential non-mixture cure fraction model is a strong competitor.
Co-Authors Adam Rabiu Jamilu Yunusa Falgore Naziru Isah Muhammad