When to use multiple imputation vs single imputation for missing data

If the fraction of missing data is sufficiently small, a common pre-processing
step is to perform imputation to fill in the missing values and proceed with
conventional methods for further processing. Any errors introduced by inaccurate
imputation may be considered insignificant in terms of the entire processing
chain. With a larger proportion of measurements being missing, errors caused
by the imputation are increasingly relevant as errors propagate in non-obvious
ways,