Missing values in longitudinal dietary data: A multiple imputation approach based on a fully conditional specification

Statistics in Medicine

Volumn 28, Issue 29, 2009, Pages 3657-3669

  Nevalainen, Jaakko ^a   Kenward, Michael G ^b   Virtanen, Suvi M ^a,c  

^a UNIVERSITY OF TAMPERE   (Finland)

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

^c NATIONAL PUBLIC HEALTH INSTITUTE   (Finland)

Author keywords

Dietary data; Fully conditional specification; Multiple imputation; Nutritional epidemiology

Indexed keywords

HLA DQB1 ANTIGEN;

ARTICLE; CASE CONTROL STUDY; DATA ANALYSIS; DISEASE PREDISPOSITION; FEEDING BEHAVIOR; FOLLOW UP; HUMAN; INFANT NUTRITION; INSULIN DEPENDENT DIABETES MELLITUS; LONGITUDINAL STUDY; MATHEMATICAL ANALYSIS; NUTRITIONAL HEALTH; OBSERVATIONAL STUDY; REGRESSION ANALYSIS; RISK ASSESSMENT; STATISTICAL ANALYSIS;

CASE-CONTROL STUDIES; COHORT STUDIES; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; DIABETES MELLITUS, TYPE 1; DIET; GENETIC PREDISPOSITION TO DISEASE; HLA-DQ ANTIGENS; HUMANS; INFANT, NEWBORN; LONGITUDINAL STUDIES;

EID: 72849117782     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3731     Document Type: Article

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