FREQUENTIST APPROACH FOR PARAMETRIC-SURVIVAL MODELS WITH APPLICATION TO RIGHT CENSORED LIVER CIRRHOSIS DATA
Abstract
The aim of this study was to fit an appropriate parametric survival model to right-censored liver cirrhosis data using the frequentist approach. Secondary data obtained from selected hospital facilities were used in this study. The collected data were analyzed using survival analysis. The Global test results confirmed that the constant hazard assumption was met. The results of the model comparison using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) revealed that the Weibull proportional hazard (PH) model and the lognormal accelerated failure time (AFT) model outperformed the other models considered in this study. Overall, the lognormal AFT model outperformed the Weibull PH model. Based on this model, it was discovered that drugs and liver status were significant predictors of survival in patients with liver cirrhosis. Based on these findings, it was recommended that patients with liver cirrhosis who were on drugs should adhere strictly to their medication and also consider regular liver function tests to ensure that their liver is in good state.
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The researcher will employ parametric PH and AFT models to determine the factors affecting the survival of patients with liver cirrhosis using the frequentist approachDownloads
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Copyright (c) 2024 Abubakar Muhammad Auwal, w.b. yahya, Daniel Victoria , Ahmed Ibrahim
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