Statistical modeling for the prediction of survival rate in a neurodegenerative disease

Statistical modeling for the prediction of survival rate in a neurodegenerative disease

A new survival model called the Marshall-Olkin Generalized Defective Gompertz Distribution (MO-GDGD) has been recently developed. We present in this paper some mathematical properties of the model. An exhaustive simulation study is conducted for various values of the parameters of MO-GDGD and differ...

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Bibliographic Details
Published in:2022 5th International Conference on Advanced Systems and Emergent Technologies (IC_ASET) pp. 245 - 249
Main Authors: Hamdeni, Tasnime, Gasmi, Soufiane, Sayadi, Mounir, Ginoux, Jean-Marc
Format: Conference Proceeding
Language:English
Published: IEEE 22-03-2022
Subjects:
Analytical models
Cure fraction
Data analysis
defective modeling
Gompertz distribution
Marshall-Olkin
Maximum likelihood estimation
Pathology
Predictive models
Sociology
Statistical analysis
survival analysis
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Summary:A new survival model called the Marshall-Olkin Generalized Defective Gompertz Distribution (MO-GDGD) has been recently developed. We present in this paper some mathematical properties of the model. An exhaustive simulation study is conducted for various values of the parameters of MO-GDGD and different sample sizes. Statistical inference methods were applied for the survival analysis of patients suffering from the neurogenerative pathology Amyotrophic Lateral Sclerosis. The type I right-censorship of the data was taken into account. Interesting results have been obtained.
DOI:10.1109/IC_ASET53395.2022.9765831