Bias and Precision of the "multiple Imputation, Then Deletion" Method for Dealing with Missing Outcome Data

American Journal of Epidemiology

Volumn 182, Issue 6, 2015, Pages 528-534

  Sullivan, Thomas R ^a   Salter, Amy B ^a   Ryan, Philip ^a   Lee, Katherine J ^b,c  

^a UNIVERSITY OF ADELAIDE   (Australia)

^b ROYAL CHILDREN'S HOSPITAL   (Australia)

^c UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

Auxiliary variables; epidemiologic methods; missing data; multiple imputation; simulation

Indexed keywords

DATA ACQUISITION; DATA INTERPRETATION; EFFICIENCY MEASUREMENT; EPIDEMIOLOGY; ESTIMATION METHOD; PRECISION; SAMPLING BIAS; SIMULATION;

ACCURACY; ARTICLE; BINOMIAL DISTRIBUTION; COMPARATIVE STUDY; CONTROLLED STUDY; DATA PROCESSING; EPIDEMIOLOGICAL DATA; LINEAR REGRESSION ANALYSIS; MULTIPLE IMPUTATION THEN DELETION METHOD; OUTCOME VARIABLE; PREDICTOR VARIABLE; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL BIAS; SYSTEMATIC ERROR; CLUSTER ANALYSIS; COMPUTER SIMULATION; HUMAN; MONTE CARLO METHOD; PROPENSITY SCORE; RANDOMIZED CONTROLLED TRIAL (TOPIC); STATISTICS AND NUMERICAL DATA; TREATMENT OUTCOME;

CLUSTER ANALYSIS; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; MONTE CARLO METHOD; PROPENSITY SCORE; RANDOMIZED CONTROLLED TRIALS AS TOPIC; TREATMENT OUTCOME;

EID: 84941659662     PISSN: 00029262     EISSN: 14766256     Source Type: Journal    
DOI: 10.1093/aje/kwv100     Document Type: Article

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