Unpredictable bias when using the missing indicator method or complete case analysis for missing confounder values: an empirical example
Journal of Clinical EpidemiologyPublished 26 March 2010
Mirjam J. Knol, Kristel J.M. Janssen, A. Rogier T. Donders, Toine C. G. Egberts, Eibert R. Heerdink, Diederick E. Grobbee
Citations181
SJR quartileQ1
SJR score3.15
SNIP2.66
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TL;DR
MIM should not be used in handling missing confounder data because it gives unpredictable bias of the odds ratio even with small percentages of missing values, and CC can be used when missing values are completely random, but it gives loss of statistical power.
Abstract
MIM should not be used in handling missing confounder data because it gives unpredictable bias of the odds ratio even with small percentages of missing values. CC can be used when missing values are completely random, but it gives loss of statistical power.
Keywords
Social SciencesMathematics
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