Hierarchical imputation of systematically and sporadically missing data: An approximate Bayesian approach using chained equations

Biometrical Journal

Volumn 60, Issue 2, 2018, Pages 333-351

  Jolani, Shahab ^a  

^a MAASTRICHT UNIVERSITY   (Netherlands)

Author keywords

conditional imputation; multilevel imputation; multiple imputation by chained equations (MICE); sequential regression imputation

Indexed keywords

RANDOM PROCESSES;

APPROXIMATE BAYESIAN; BAYESIAN APPROACHES; CLUSTERED DATUM; CONDITIONAL IMPUTATION; MISSING DATA; MULTILEVEL IMPUTATION; MULTILEVELS; MULTIPLE IMPUTATION; MULTIPLE IMPUTATION BY CHAINED EQUATION; SEQUENTIAL REGRESSION IMPUTATION;

BAYESIAN NETWORKS;

BAYES THEOREM; BIOMETRY; FEMALE; GLOMERULUS FILTRATION RATE; HUMAN; KIDNEY FAILURE; MALE; PATHOPHYSIOLOGY; PROCEDURES; PROGNOSIS; SOFTWARE;

BAYES THEOREM; BIOMETRY; FEMALE; GLOMERULAR FILTRATION RATE; HUMANS; MALE; PROGNOSIS; RENAL INSUFFICIENCY; SOFTWARE;

EID: 85030710828     PISSN: 03233847     EISSN: 15214036     Source Type: Journal    
DOI: 10.1002/bimj.201600220     Document Type: Article

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