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http://hdl.handle.net/10419/31126
  
Title:A Bayesian semiparametric latent variable model for mixed responses PDF Logo
Authors:Fahrmeir, Ludwig
Raach, Alexander
Issue Date:2006
Series/Report no.:Discussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München 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 variable are modelles 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.
Subjects:Latent variable models
mixed responses
penalized splines
spatial effects
MCMC
Persistent Identifier of the first edition:urn:nbn:de:bvb:19-epub-1839-8
Document Type:Working Paper
Appears in Collections:Discussion papers, SFB 386, LMU München

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