کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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415886 | 681253 | 2011 | 19 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: A mixture of generalized latent variable models for mixed mode and heterogeneous data A mixture of generalized latent variable models for mixed mode and heterogeneous data](/preview/png/415886.png)
In the behavioral, biomedical, and social–psychological sciences, mixed data types such as continuous, ordinal, count, and nominal are common. Subpopulations also often exist and contribute to heterogeneity in the data. In this paper, we propose a mixture of generalized latent variable models (GLVMs) to handle mixed types of heterogeneous data. Different link functions are specified to model data of multiple types. A Bayesian approach, together with the Markov chain Monte Carlo (MCMC) method, is used to conduct the analysis. A modified DIC is used for model selection of mixture components in the GLVMs. A simulation study shows that our proposed methodology performs satisfactorily. An application of mixture GLVM to a data set from the National Longitudinal Surveys of Youth (NLSY) is presented.
Journal: Computational Statistics & Data Analysis - Volume 55, Issue 11, 1 November 2011, Pages 2889–2907