Self perceived health status of schizophrenic patients in Spain: an analysis of geog raphical differences using bayesian approach

Objectives. This paper explores the use of regression models for estimating health status of schizophrenic patients, from a Bayesian perspective. Our aims are: 1- To obtain a set of values of health states of the EQ-5D based on self-assessed health from a sample of schizophrenic patients. 2- To analyse the differences in the health status and in patients’ perceptions of their health status between four mental-health districts in Spain. Methods. We develop two linear models with dummy variables. The first model seeks to obtain an index of the health status of the patients using a VAS as a dependent variable and the different dimensions of EQ-5D as regressors. The second model allows to analyse the differences between the self-assessed health status in the different geographic areas and also the differences between the patients’ self-assessed health states, irrespective of their actual health state, in the different geographic areas. The analysis is done using Bayesian approach with Gibbs sampling (computer program WinBUGS 1.4). Data concerning self-assessed EQ-5D with VAS from four geographic areas of schizophrenic patients were obtained for the purposes of this analysis. Results. We obtained the health status index for this sample and analysed the differences for this index between the four geographic areas. Our study reveals variables that explain the differences in patients’ health status and differences in their health states assessment. We consider four possible scenarios.

Market allocations of location choice: an example

The purpose of this paper is to make an example which, first, illustrates Starret’s Spatial Imposibility Theorem, when agents have free mobility; and second, allowes us to get a competitive equilibrium with transportation when agents move only if there is a noticeable difference in utilities that justifies the change of location.