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Left, right, midpoint and random point Imputation techniques for Weibull regression model with right and interval-censored data

The research explores several imputation techniques, namely left, right, midpoint and random imputations for the MLE of the Weibull regression model with covariate for uncensored, right, and interval-censored data. A simulation study is conducted to obtain the parameter estimates of the model with d...

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Main Authors: Naushad Ali, Ahmad Kabeer, Arasan, Jayanthi
Format: Article
Language:English
Published: Universiti Malaysia Perlis 2024
Online Access:http://psasir.upm.edu.my/id/eprint/115408/1/115408.pdf
http://psasir.upm.edu.my/id/eprint/115408/
https://ejournal.unimap.edu.my/index.php/amci/article/view/330
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spelling my.upm.eprints.1154082025-03-04T03:19:31Z http://psasir.upm.edu.my/id/eprint/115408/ Left, right, midpoint and random point Imputation techniques for Weibull regression model with right and interval-censored data Naushad Ali, Ahmad Kabeer Arasan, Jayanthi The research explores several imputation techniques, namely left, right, midpoint and random imputations for the MLE of the Weibull regression model with covariate for uncensored, right, and interval-censored data. A simulation study is conducted to obtain the parameter estimates of the model with different imputation techniques, sample sizes, and censoring proportions and its performance are evaluated using bias, standard error (SE), and root mean square error (RMSE). The simulation result indicates that midpoint imputation technique outperformed other techniques based on the lowest RMSE values. Finally, the model was fit to diabetic nephropathy data were fitted to the model using selected imputation techniques. The result concluded that the Weibull regression model may provide a good fit to the data and that the covariate, gender has a significant effect on the survival time of patient kidneys. Universiti Malaysia Perlis 2024 Article PeerReviewed text en cc_by_nc_sa_4 http://psasir.upm.edu.my/id/eprint/115408/1/115408.pdf Naushad Ali, Ahmad Kabeer and Arasan, Jayanthi (2024) Left, right, midpoint and random point Imputation techniques for Weibull regression model with right and interval-censored data. Applied Mathematics and Computational Intelligence (AMCI), 13 (3). pp. 115-142. ISSN 2289-1323; eISSN: 2289-1315 https://ejournal.unimap.edu.my/index.php/amci/article/view/330 10.58915/amci.v13i3.330
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description The research explores several imputation techniques, namely left, right, midpoint and random imputations for the MLE of the Weibull regression model with covariate for uncensored, right, and interval-censored data. A simulation study is conducted to obtain the parameter estimates of the model with different imputation techniques, sample sizes, and censoring proportions and its performance are evaluated using bias, standard error (SE), and root mean square error (RMSE). The simulation result indicates that midpoint imputation technique outperformed other techniques based on the lowest RMSE values. Finally, the model was fit to diabetic nephropathy data were fitted to the model using selected imputation techniques. The result concluded that the Weibull regression model may provide a good fit to the data and that the covariate, gender has a significant effect on the survival time of patient kidneys.
format Article
author Naushad Ali, Ahmad Kabeer
Arasan, Jayanthi
spellingShingle Naushad Ali, Ahmad Kabeer
Arasan, Jayanthi
Left, right, midpoint and random point Imputation techniques for Weibull regression model with right and interval-censored data
author_facet Naushad Ali, Ahmad Kabeer
Arasan, Jayanthi
author_sort Naushad Ali, Ahmad Kabeer
title Left, right, midpoint and random point Imputation techniques for Weibull regression model with right and interval-censored data
title_short Left, right, midpoint and random point Imputation techniques for Weibull regression model with right and interval-censored data
title_full Left, right, midpoint and random point Imputation techniques for Weibull regression model with right and interval-censored data
title_fullStr Left, right, midpoint and random point Imputation techniques for Weibull regression model with right and interval-censored data
title_full_unstemmed Left, right, midpoint and random point Imputation techniques for Weibull regression model with right and interval-censored data
title_sort left, right, midpoint and random point imputation techniques for weibull regression model with right and interval-censored data
publisher Universiti Malaysia Perlis
publishDate 2024
url http://psasir.upm.edu.my/id/eprint/115408/1/115408.pdf
http://psasir.upm.edu.my/id/eprint/115408/
https://ejournal.unimap.edu.my/index.php/amci/article/view/330
_version_ 1825810745783222272
score 13.244413

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