Multiple imputation methods for handling missing data in cost-effectiveness analyses that use data from hierarchical studies: An application to cluster randomized trials

Medical Decision Making

Volumn 33, Issue 8, 2013, Pages 1051-1063

  Gomes, Manuel ^a   Díaz Ordaz, Karla ^a   Grieve, Richard ^a   Kenward, Michael G ^a  

^a LONDON SCHOOL OF HYGIENE AND TROPICAL MEDICINE   (United Kingdom)

Author keywords

cluster randomized trials; cost effectiveness analysis; hierarchical data; missing data; multiple imputation

Indexed keywords

ARTICLE; CLUSTER ANALYSIS; CLUSTER RANDOMIZED TRIALS; COST BENEFIT ANALYSIS; COST-EFFECTIVENESS ANALYSIS; HIERARCHICAL DATA; MISSING DATA; MULTIPLE IMPUTATION; RANDOMIZED CONTROLLED TRIAL (TOPIC); STATISTICAL ANALYSIS;

CLUSTER RANDOMIZED TRIALS; COST-EFFECTIVENESS ANALYSIS; HIERARCHICAL DATA; MISSING DATA; MULTIPLE IMPUTATION;

CLUSTER ANALYSIS; COST-BENEFIT ANALYSIS; DATA INTERPRETATION, STATISTICAL; RANDOMIZED CONTROLLED TRIALS AS TOPIC;

MLCS; MLOWN;

EID: 84886052495     PISSN: 0272989X     EISSN: 1552681X     Source Type: Journal    
DOI: 10.1177/0272989X13492203     Document Type: Article

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