Simulation of parametric model towards the fixed covariate of right censored lung cancer data

In this study, simulation procedure was applied to measure the fixed covariate of right censored data by using parametric survival model. The scale and shape parameter were modified to differentiate the analysis of parametric regression survival model. Statistically, the biases, mean biases and the...

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Bibliographic Details
Main Authors: Muhamad Jamil, Siti Afiqah, Abdullah, M. Asrul Affendi, Kek, Sie Long, Olaniran, Oyebayo Ridwan, Amran, Syahila Enera
Format: Article
Language:English
Published: IOP Publishing 2017
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Online Access:http://eprints.uthm.edu.my/5167/1/AJ%202017%20%28297%29%20Simulation%20of%20parametric%20model%20towards%20the%20fixed%20covariate.pdf
http://eprints.uthm.edu.my/5167/
http://dx.doi.org/10.1088/1742-6596/890/1/012172
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Institution: Universiti Tun Hussein Onn Malaysia
Language: English
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Summary:In this study, simulation procedure was applied to measure the fixed covariate of right censored data by using parametric survival model. The scale and shape parameter were modified to differentiate the analysis of parametric regression survival model. Statistically, the biases, mean biases and the coverage probability were used in this analysis. Consequently, different sample sizes were employed to distinguish the impact of parametric regression model towards right censored data with 50, 100, 150 and 200 number of sample. R-statistical software was utilised to develop the coding simulation with right censored data. Besides, the final model of right censored simulation was compared with the right censored lung cancer data in Malaysia. It was found that different values of shape and scale parameter with different sample size, help to improve the simulation strategy for right censored data and Weibull regression survival model is suitable fit towards the simulation of survival of lung cancer patients data in Malaysia.