| Issue |
ITM Web Conf.
Volume 67, 2024
The 19th IMT-GT International Conference on Mathematics, Statistics and Their Applications (ICMSA 2024)
|
|
|---|---|---|
| Article Number | 01037 | |
| Number of page(s) | 12 | |
| Section | Mathematics, Statistics and Their Applications | |
| DOI | https://doi.org/10.1051/itmconf/20246701037 | |
| Published online | 21 August 2024 | |
Investigating accuracy of biomarker involving a parametric approach of proportional hazard skewed normal model
Universiti Teknologi Malaysia, Department of Mathematics, Faculty of Science, 81310 Skudai, Johor, Malaysia
* Corresponding author: ahmad97@graduate.utm.my
Time-dependent receiver operating characteristic (ROC) curve is useful to measure the accuracy performance over time. In this paper, we have shown how to determine the accuracy trend using proportional hazard model with continuous skewed normal biomarker and skewed normal time-to-event. Bayesian inference and adaptive multivariate integration over hypercubes are used respectively for parameter estimation and solving the sensitivity and specificity of the time-dependent ROC. The simulation study and application on real data suggest that it is possible to predict the accuracy measurement over time by changing the estimated association parameter between the biomarker and time-to-event data. In addition, studies on the impact of sample size on the ROC curve shows an advantage of this parametric method over conventional nonparametric.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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