S3RI Seminar - "Bayesian inference for bivariate copulas with additive models for dependence, marginal location, scale and shape: an application in paediatric ophthalmology", Prof Mario Cortina Borja (University College London) Seminar

Event details

Motivated by data on visual acuity from a large sample of children aged between 3 and 8 years, we propose bivariate copula models with dependence parameters, and sinh-arcsinh marginal densities with location, scale and shape parameters that depend on a covariate through additive models. We perform inference about the unknown quantities of our model in the Bayesian framework using a Markov chain Monte Carlo algorithm. We apply our model to paediatric ophthalmic data to gain new insights about the processes which cause changes in visual acuity with respect to age, including the age-related nature of the copula dependence parameter. We analyse predictive distributions to identify children with unusual sight characteristics, distinguishing those who are bivariate, but not univariate outliers. In this way we provide an innovative tool that enables clinicians to identify children with unusual sight who may otherwise be missed.