Imputation methods for exponential survival model via partly interval-censored data

Survival analysis is a collection of statistical approaches for data analysis when the outcome variable of interest is the time until an event occurs. The time to failure of an experimental unit may be censored and this can be right, left, interval, and Partly Interval Censored (PIC). PIC contain th...

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Bibliographic Details
Main Authors: Umer, Salman, Elfaki, Faiz, Zyoud, Abdullah
Format: Conference Proceeding
Language:English
Subjects:
Censored data (mathematics)
Data analysis
Simulation
Survival
Online Access:Get full text
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Summary:Survival analysis is a collection of statistical approaches for data analysis when the outcome variable of interest is the time until an event occurs. The time to failure of an experimental unit may be censored and this can be right, left, interval, and Partly Interval Censored (PIC). PIC contain the exact observations and interval-censored. In this paper, more than 25% of exact observations from the medical simulation data set will be used based on the exponential survival model via the imputation techniques. In addition to that, Multiple Imputation (MI) will be compared to the left imputation via the simulation study. The result of this simulation study suggested that for more exact observations, the results are well performed and easily implemented especially for the MI method.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0195520