Using beta regression modeling in medical sciences: a comparative study
Abstract
Beta regression (BR) models provide an adequate approach for modeling continuous outcomes of limited intervals (0, 1). The BR model assumes that the dependent variable follows a beta distribution and that its mean is affiliated to a set of exploratory variables through a linear predictor known as coefficients and link function. The BR model also includes a dispersion parameter. This paper describes the BR model along with its properties. Furthermore, the comparison between different link functions of the BR model is conducted through a medical real-life application to laparoscopic surgical operations aiming to widen congenital obstruction in the connection between the kidney and ureter, a condition called ureteropelvic junction obstruction (UJO).
- Published
- 20 February 2023
- Volume
- 2023 (2023)
- License
- CC BY 3.0
Copyright © 2023 Mohamed R. Abonazel, Hadir A. Said, Elsayed Tag-Eldin, Suzan Abdel-Rahman, Ibrahim G. Khattab. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cite this article
M. R. Abonazel, H. A. Said, E. Tag-Eldin, S. Abdel-Rahman, I. G. Khattab, Using beta regression modeling in medical sciences: a comparative study, Commun. Math. Biol. Neurosci. 2023 (2023), 18. https://doi.org/10.28919/cmbn/6144
BibTeX
@article{Abonazel2023,
author = {Abonazel, Mohamed R. and Said, Hadir A. and Tag-Eldin, Elsayed and Abdel-Rahman, Suzan and Khattab, Ibrahim G.},
title = {Using beta regression modeling in medical sciences: a comparative study},
journal = {Commun. Math. Biol. Neurosci.},
volume = {2023},
year = {2023},
pages = {18},
doi = {10.28919/cmbn/6144}
}