Strategies for multiple imputation in longitudinal studies

American Journal of Epidemiology

Volumn 172, Issue 4, 2010, Pages 478-487

  Spratt, Michael ^a   Carpenter, James ^b   Sterne, Jonathan A C ^a   Carlin, John B ^c,d   Heron, Jon ^a   Henderson, John ^a   Tilling, Kate ^a  

^a UNIVERSITY OF BRISTOL   (United Kingdom)

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

^c ROYAL CHILDREN'S HOSPITAL   (Australia)

^d UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

imputation; longitudinal studies; missing data

Indexed keywords

ASTHMA; CHILD HEALTH; DATA SET; DISEASE PREVALENCE; EPIDEMIOLOGY; ERROR ANALYSIS; LONGITUDINAL GRADIENT; MONTE CARLO ANALYSIS; NUMERICAL MODEL; PARTICIPATORY APPROACH; PRECISION; SMOKING;

ACCURACY; ARTICLE; ASTHMA; CHILD; DATA ANALYSIS; DISEASE ASSOCIATION; FEMALE; GENDER; HUMAN; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; MALE; MATERNAL DISEASE; MATERNAL SMOKING; MULTIPLE IMPUTATION; OUTCOME ASSESSMENT; PRESCHOOL CHILD; PREVALENCE; STATISTICAL ANALYSIS; STRATEGIC PLANNING; WHEEZING; COMPLICATION; RESPIRATORY SOUNDS; STATISTICAL BIAS; STATISTICAL MODEL; UNITED KINGDOM;

ASTHMA; BIAS (EPIDEMIOLOGY); CHILD; GREAT BRITAIN; HUMANS; LOGISTIC MODELS; LONGITUDINAL STUDIES; MODELS, STATISTICAL; PREVALENCE; RESPIRATORY SOUNDS;

AVON; ENGLAND; UNITED KINGDOM;

EID: 77955896455     PISSN: 00029262     EISSN: 14766256     Source Type: Journal    
DOI: 10.1093/aje/kwq137     Document Type: Article

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