A Comparison of Bayesian Mixed Data Models for Austrian SILC data
DOI:
https://doi.org/10.17713/ajs.v43i2.35Abstract
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.
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