When managing missing data, how many questions should participant have completed, at a minimum, before imputing the remainder of their missing data?
For example, a number of my participants only completed demographic variables, but failed to complete any of standardised assessment measures (so no dependent or independent variables were completed). It seems illogical to include these people in multiple imputation (or other method) as they are essentially missing
>90% of their data, but would need to justify this and don't know how.
I completed Little's MCAR test and data was actually
MCAR and is also missing monotonically. I also completed
Chi-square analyses to look for demographic differences between those who completed at least one standard measure and those who didn't, with no significant findings.