Semiparametric Bayesian analysis of structural equation models with fixed covariates

Statistics in Medicine

Volumn 27, Issue 13, 2008, Pages 2341-2360

  Lee, Sik Yum ^a   Lu, Bin ^b   Song, Xin Yuan ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^b NANJING UNIVERSITY   (China)

Author keywords

Blocked Gibbs sampler; Dirichlet process; Latent variables; Semiparametric hierarchical modeling; Stick breaking prior

Indexed keywords

CREATININE; GLUCOSE; HEMOGLOBIN A1C; HIGH DENSITY LIPOPROTEIN; LOW DENSITY LIPOPROTEIN; TRIACYLGLYCEROL;

AGE; ARTICLE; BAYES THEOREM; COMPUTER SIMULATION; COVARIANCE; CREATININE BLOOD LEVEL; DIABETIC NEPHROPATHY; DIABETIC PATIENT; DISEASE SEVERITY; GLUCOSE BLOOD LEVEL; HUMAN; KIDNEY DISEASE; LIPOPROTEIN BLOOD LEVEL; MATHEMATICAL ANALYSIS; METHODOLOGY; PATHOPHYSIOLOGY; PROBABILITY; RISK ASSESSMENT; RISK FACTOR; SAMPLE SIZE; SAMPLER; SMOKING; STRUCTURAL EQUATION MODELING; TRIACYLGLYCEROL BLOOD LEVEL;

ALBUMINURIA; BAYES THEOREM; COMPUTER SIMULATION; CREATININE; DIABETES MELLITUS, TYPE 2; DIABETIC NEPHROPATHIES; HUMANS; MODELS, BIOLOGICAL; MODELS, STATISTICAL;

EID: 44949196885     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3098     Document Type: Article

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