Page 102 - programme book

ST-028
Generalized Exponential Distribution with Interval-Censored Data and
Time Dependent Covariate

Hussein Ali AL-Hakeem 1, a) , Jayanthi Arasan 2, b) , Mohd Shafie Bin Mustafa 2, c) and Lim Fong
Peng 2, d)

1 Institute for Mathematical Research, Universiti Putra Malaysia,
43400 UPM Serdang, Selangor, Malaysia.
2 Department of Mathematics, Faculty of Science, Universiti Putra Malaysia,
43400 UPM Serdang, Selangor, Malaysia.

a) Corresponding author: ha828147@gmail.com
b) jayanthi@upm.edu.my
c) mshafie@upm.edu.my
d) fongpeng@upm.edu.my

Abstract. This study will improve the performance of the Generalized Exponential Distribution
(GED) by incorporating time-dependent covariates (TD) in the presence of interval-censored data.
Interval-censored data usually arises in clinical and epidemiological studies where lifetime is only
known to fall within an interval. Moreover, this study concentrates on the parameter’s estimation for
this distribution. This study will compare the maximum likelihood estimation (MLE) for two distinct
models, namely time-dependent covariates model and time independent covariates model in terms of
their bias, standard error (SE) and root mean square error (RMSE) at various attendance probability
(AP) and sample sizes. The results indicate that bias, SE and RMSE values of the parameter estimates
increase with the increase in attendance probability and decrease with the increase in sample size.

Keywords: Generalized exponential distribution (GED), Interval censoring, Time-dependent
covariates, Time-independent covariates, MLE.

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