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Dealing with missing data in covariates: The missing indicator method
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Doi:
10.20982/tqmp.20.3.p032
Jolani, Shahab
, Weinstein, Pawel
v32-v38
Keywords:
Imputation
, Missing data
, Observational studies
, Randomization
Tools: R, SPSS
(no sample data)
 
(no appendix)
This vignette presents the missing indicator method for handling missing data in covariates. The method unfolds through two activities, guiding students in the practical implementation of the method and comparable alternatives using statistical software. We further evaluate these activities and discuss conditions under which the missing indicator method yields valid results. We conclude that the missing indicator method can be safely used in experimental studies characterized by randomization protocols.
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