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...

詳細記述

書誌詳細
出版年:Austrian Journal of Statistics
第一著者: 2-s2.0-85083303856
フォーマット: 論文
言語:English
出版事項: Austrian Statistical Society 2020
オンライン・アクセス:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083303856&doi=10.17713%2fajs.v49i3.1085&partnerID=40&md5=d2f5900d940fbdb3a14ae6d91d6130bd
その他の書誌記述
要約: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.
ISSN:1026597X
DOI:10.17713/ajs.v49i3.1085