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ERIC Number: EJ1158738
Record Type: Journal
Publication Date: 2017-Nov
Pages: 28
Abstractor: As Provided
ISSN: ISSN-0049-1241
Bayesian Adaptive Lasso for Ordinal Regression with Latent Variables
Feng, Xiang-Nan; Wu, Hao-Tian; Song, Xin-Yuan
Sociological Methods & Research, v46 n4 p926-953 Nov 2017
We consider an ordinal regression model with latent variables to investigate the effects of observable and latent explanatory variables on the ordinal responses of interest. Each latent variable is characterized by correlated observed variables through a confirmatory factor analysis model. We develop a Bayesian adaptive lasso procedure to conduct simultaneous estimation and variable selection. Nice features including empirical performance of the proposed methodology are demonstrated by simulation studies. The model is applied to a study on happiness and its potential determinants from the Inter-university Consortium for Political and Social Research.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A