Sensitivity analysis for variance parameters in Bayesian simplex mixed models for proportional data

In this article, we present a Bayesian modeling for response variables restricted to the interval (0, 1), such as proportions and rates, using the simplex distribution for cases in which data have a longitudinal form, taking random effects into account. In order to investigate the stability of posterior distribution, we study through sensitivity analysis, the effect of three different uniparametric prior distributions for variance parameters of random effect on the final estimation. For this purpose, we consider homogeneous and heterogeneous structures for parameters in location and dispersion submodels. Models and results are illustrated with simulated and real data application.