Aplicações em meta-análise sob um enfoque bayesiano usando dados médicos

Abstract

In this work, we consider the use of Meta-analysis with a Bayesian approach. Meta-analysis is a statistical technique that combines the results of di¤erent independent studies with purpose to find general conclusions. This term was introduced by Glass (1976) and it has been used when the number of studies about some research project is small. Usually, the models for Meta-analysis assume a large number of parameters and the Bayesian approach using MCMC (Markov Chain Monte Carlo) methods is a good alternative to combine information of independent studies, to obtain accutrate inferences about a specified treatment. As illustration, we consider real medical data sets on di¤erent studies, in which, we consider fixed and random e¤ects models. We also assume mixture of normal distributions for the error of the models. Another application is considered with educational data.