Work

Two-stage circular-circular regression with zero inflation: Application to medical sciences

Year: 2021

Type: article

Abstract: This paper considers the modeling of zero-inflated circular measurements concerning real case studies from medical sciences. Circular-circular regression models have been discussed in the statistical literature and illustrated with various real-life applications. However, there are no models to deal with zero-inflated response as well as a covariate simultaneously. The Möbius transformation based two-stage circular-circular regression model is proposed, and the Bayesian estimation of the model parameters is suggested using the MCMC algorithm. Simulation results show the superiority of the performance of the proposed method over the existing competitors. The method is applied to analyse real datasets on astigmatism due to cataract surgery and abnormal gait related to orthopaedic impairment. The methodology proposed can assist in efficient decision making during treatment or postoperative care.

Source: The Annals of Applied Statistics

DOI: 10.1214/20-aoas1429

Authors: Jayant Jha, Prajamitra Bhuyan

Institutions: Aix-Marseille Université, Institut de Neurosciences des Systèmes, Imperial College London

Language: English

Topic: Statistical Distribution Estimation and Applications

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

Funder: Lloyd's Register