Estimate Parametric Regression Models Depend on (Time-To-Event) Survival Time Distributions with Application
Keywords:
Survival Analysis, parametric regression models, Maximum likelihood estimation (MLE, prostate Cancer, Accelerated Failure Time (AFTAbstract
The aim of this study is to compare between the parametric regression models estimated according to the distributions of survival time and select the best appropriate model for the distribution of survival time and estimate its parameters. Use parametric regression models for data and determine the factors that affect the survival time of patients. The study was applied to a sample size of (120) patients with prostate cancer / Hiwa Hospital in Sulaymaniyah Governorate for a period from January 1, 2019 to November 1, 2021.
The best model was determined based on each of the criteria AIC and BIC and using the applications (Mat-lab, Stata 15.1, Easy Fit 5.6). The result show that the best model is (Weibull-AFT) and the factors (Age, PSA, Stage, metastasis) are that affect the patient's survival time.
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