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Parametric proportional hazard models using the Bayesian approach with applications to healthcare data | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 2، دوره 14، شماره 4، تیر 2023، صفحه 15-36 اصل مقاله (1.39 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2023.31047.4194 | ||
| نویسندگان | ||
| Sanaa Noor Mohammed Al-Sharifi* ؛ Tasnim Hasan Kadhim AlBaldawi | ||
| Department of Mathematics, College of Science, University of Baghdad, Iraq | ||
| تاریخ دریافت: 29 آبان 1401، تاریخ بازنگری: 26 دی 1401، تاریخ پذیرش: 07 اسفند 1401 | ||
| چکیده | ||
| The aim of this study is on using Bayesian inference to analyze right-censored healthcare data using Frechet and exponential baseline proportional hazard (PH) models. For the baseline hazard parameters, a gamma prior was used, and for the regression coefficients, normal priors were used. The exact form of the joint posterior distribution was obtained. Bayes estimators of the parameters are obtained using the Markov chain Monte Carlo (MCMC) simulation technique. Two real-survival data applications were analyzed by the Frechet PH model and the exponential PH model. The convergence diagnostic tests are presented. We found that the Frechet PH model was better than the exponential PH model because it is flexible and could be beneficial in analyzing survival data. | ||
| کلیدواژه‌ها | ||
| Proportional hazards model؛ Frechet distribution؛ exponential distribution؛ Bayesian inference؛ MCMC | ||
| مراجع | ||
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