TWO-STAGE CIRCULAR-CIRCULAR REGRESSION WITH ZERO INFLATION: APPLICATION TO MEDICAL SCIENCES

• 成果类型: Article
• 署名作者: Jha, Jayant; Bhuyan, Prajamitra
• 署名单位: Aix-Marseille Universite; Assistance Publique-Hopitaux de Marseille; Institut National de la Sante et de la Recherche Medicale (Inserm); Imperial College London
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/20-AOAS1429
• 发表日期: 2021
• 页码: 1343-1365
• 关键词: vision impairment; bayesian-analysis; blindness; astigmatism; population; spike; BIAS

摘要

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 Mobius 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.