A Bayesian Semiparametric Latent Variable Model for Mixed Responses

Autor/inn/en	Fahrmeir, Ludwig; Raach, Alexander
Titel	A Bayesian Semiparametric Latent Variable Model for Mixed Responses
Quelle	In: Psychometrika, 72 (2007) 3, S.327-346 (20 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0033-3123
DOI	10.1007/s11336-007-9010-7
Schlagwörter	Markov Processes; Social Sciences; Monte Carlo Methods; Bayesian Statistics; Models; Surveys; Foreign Countries; Germany + Suchen Sie Ihr Suchwort? Markowscher Prozess; Social science; Sozialwissenschaften; Gesellschaftswissenschaften; Monte-Carlo-Methode; Analogiemodell; Survey; Umfrage; Befragung; Ausland; Deutschland
Abstract	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 semiparametric 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. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10