Multiple imputation using linked proxy outcome data resulted in important bias reduction and efficiency gains: a simulation study

Multiple imputation using linked proxy outcome data resulted in important bias reduction and efficiency gains: a simulation study

Abstract Background When an outcome variable is missing not at random (MNAR: probability of missingness depends on outcome values), estimates of the effect of an exposure on this outcome are often biased. We investigated the extent of this bias and examined whether the bias can be reduced through in...

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Bibliographic Details
Main Authors: R. P. Cornish, J. Macleod, J. R. Carpenter, K. Tilling
Format: Article
Language:English
Published: BMC 2017-12-01
Series:Emerging Themes in Epidemiology
Subjects:
Missing data
Multiple imputation
Bias
Simulation study
ALSPAC
Data linkage
Online Access:http://link.springer.com/article/10.1186/s12982-017-0068-0

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