A Bayesian semiparametric latent variable model for mixed responses

Fahrmeir, Ludwig und Raach, Alexander (2006): A Bayesian semiparametric latent variable model for mixed responses. Sonderforschungsbereich 386, Discussion Paper 471

Abstract

In this article 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 semiparametric predictor. We extend existing LVM with simple 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 large German social science survey which motivated our methodological development.

• Dokumententyp: Paper
• Keywords: Latent variable models, mixed responses, penalized splines, spatial effects, MCMC
• Fakultät: Mathematik, Informatik und Statistik > Statistik > Sonderforschungsbereich 386 ; Sonderforschungsbereiche > Sonderforschungsbereich 386
• Themengebiete: 500 Naturwissenschaften und Mathematik > 510 Mathematik
• Sprache: Englisch