A Comparison of Bayesian Mixed Data Models for Austrian SILC data

Authors

  • Helga Wagner Johannes Kepler University
  • Regina Tüchler Wirtschaftskammer Österreich

DOI:

https://doi.org/10.17713/ajs.v43i2.35

Abstract

In many applications multidimensional outcome variables measured on different scales are of interest. In this paper we consider regression modelling of a bivariate response with a normal and a binary component. We use three different approaches to model dependence: a joint logit-normal model for the two responses, a factorization model with linear dependence and a    a factorization model with flexible non-linear dependence. We apply these approaches to Austrian SILC data to analyse material deprivation and household income.

Published

2014-06-12

How to Cite

Wagner, H., & Tüchler, R. (2014). A Comparison of Bayesian Mixed Data Models for Austrian SILC data. Austrian Journal of Statistics, 43(2), 103-117. https://doi.org/10.17713/ajs.v43i2.35

Issue

Section

Articles