Abstract
Survival analysis or time-to-event analysis refers to a set of methods to analyze the time between entry to a study and a subsequent event where time to failure of an experimental unit and that could be one of the main types of censored such as Partly Interval-Censored (PIC). In this paper, the
likelihoods are applied to estimate the function of survival and parameters in the exponential model when imputation methods such as Multiple Imputation (MI) and Left Imputation (LI) in the present of PIC data. The numerical evidence via simulated breast cancer data suggests that the estimates from MI are more accurate than the LI in the present of PIC data. In additional to that the patient who received chemotherapy and hormone treatment has greater survival rate than a patient who did not receive both treatments.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
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Creators: | Creators Email / ID Num. Umer, Salman su1305814@qu.edu.qa Elfaki, Faiz felfaki@qu.edu.qa |
Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > Matrix analytic methods Q Science > QA Mathematics > Mathematical statistics. Probabilities > Data processing |
Divisions: | Universiti Teknologi MARA, Kedah |
Event Title: | e-Proceedings of the 5th International Conference on Computing, Mathematics and Statistics (iCMS 2021) |
Event Dates: | 4-5 August 2021 |
Page Range: | pp. 173-180 |
Keywords: | Partly interval-censored, exponential model, multiple imputations |
Date: | 2021 |
URI: | https://ir.uitm.edu.my/id/eprint/56169 |