Journal
PSYCHOMETRIKA
Volume 72, Issue 3, Pages 327-346Publisher
SPRINGER
DOI: 10.1007/s11336-007-9010-7
Keywords
latent variable models; mixed responses; penalized splines; spatial effects; MCMC
Ask authors/readers for more resources
In this paper we introduce a latent variable model (LVM) for mixed ordinal and continuous responses, where covariate effects on the continuous latent variables are modelled through a flexible semi-parametric Gaussian regression model. We extend existing LVMs with the usual linear covariate effects by including nonparametric components for nonlinear effects of continuous covariates and interactions with other covariates as well as spatial effects. Full Bayesian modelling is based on penalized spline and Markov random field priors and is performed by computationally efficient Markov chain Monte Carlo (MCMC) methods. We apply our approach to a German social science survey which motivated our methodological development.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available