Bayesian Sequential Estimation of Proportion of Orthopaedic Surgery Among Different Age Groups: A Case Study of National Orthopaedic Hospital, Igbobi-Nigeria

Abstract

Bayesian methods provide more intuitive and meaningful inferences than likelihood-only based inferences. This is simply because Bayesian approach includes prior information as well as likelihood. In empirical Bayes (EB) methodology, we use data to help determine the prior through estimation of the so-called hyperparameters. In this paper, a Bayesian model called Beta-binomial conjugate model is employed using Bayesian sequential estimation method to estimate the proportion of different age groups attended to at the National Orthopaedic hospital, Igbobi, Nigeria. Over the years results show that the highest number of patients at the hospital is within the age group 15 to 44 years but with the smallest proportion of orthopaedic surgeries. Similarly, smallest the numbers of patients are among the age group less than one year and greater than 64 years but with highest proportion of orthopaedic surgeries. Also, overall EB proportion of patients admitted for orthopaedic surgeries in the hospital across the age groups increased steadily. Finally, the results of the comparative analysis of the sample and EB proportions show that the EB estimators are better estimators on the basis of efficiency and consistency.