Assessing the goodness of fit of the gompertz model in the presence of right and interval censored data with covariate

This research focuses on assessing the goodness of fit for the Gompertz model in the presence of right and interval censored data with covariate. The performance of the maximum likelihood estimates was evaluated via a simulation study at various censoring proportions and sample sizes. The conclusion...

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التفاصيل البيبلوغرافية
الحاوية / القاعدة:Austrian Journal of Statistics
المؤلف الرئيسي: 2-s2.0-85083303856
التنسيق: مقال
اللغة:English
منشور في: Austrian Statistical Society 2020
الوصول للمادة أونلاين:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083303856&doi=10.17713%2fajs.v49i3.1085&partnerID=40&md5=d2f5900d940fbdb3a14ae6d91d6130bd
الوصف
الملخص:This research focuses on assessing the goodness of fit for the Gompertz model in the presence of right and interval censored data with covariate. The performance of the maximum likelihood estimates was evaluated via a simulation study at various censoring proportions and sample sizes. The conclusions were drawn based on the results of bias, standard error and root mean square error at different settings. Following that, another simulation study was carried out to compare the performance of the proposed modifications to the Cox-Snell residuals for both censored and uncensored observations at different combinations of sample sizes and censoring levels. The results show that standard error and root mean square error values of the parameter estimates increase with the increase in censoring proportions and decrease in the number of sample size. This indicates that the estimates perform better when sample sizes are larger and censoring proportions are lower. The performance of the proposed modifications of the Cox-Snell residuals showed that they perform slightly better than existing method. © 2020, Austrian Statistical Society. All rights reserved.
تدمد:1026597X
DOI:10.17713/ajs.v49i3.1085