Building a semi-parametric regression model using circular data

Abstract

Maintaining visual function requires improving it by understanding refractive error and age-related changes. The human eye acts as an optical system that focuses visual images on the retina. Refractive error is one of the main causes of retinal image deterioration in uncorrected eyes (Namba, H., Sugano & others, 2020). Source: Age-astigmatism relationship

The aim of the research is to build a semiparametric regression model using the integrated circular-linear-circular semiparametric model by integrating the parameter part estimated by the maximum likelihood method and assuming a random error with a joint distribution (linear-circular) and the nonparametric part estimated using different circular kernel functions by the integration parameter (α), . Visual data were used and obtained from (Al Noor Specialized Center for Ophthalmology and Eye Surgery) in Thi Qar Governorate using (Auto Kerato – Refracto Tonometer TOPCON TRK. 2P) device. The study sample included (400 cases) representing the data of measuring the right eye (OD cyl axis) and the left eye (OD cyl axis) and the age of the case (Patient Age) for people suffering from refractive error (Refractive Errer).