Advised missing data method

No longitudinal analysis > MNAR > <50% missing data > >75% missing item scores

The methods that are presented and discussed on this website (e.g., multiple imputation), assume a Missing at Random (MAR) mechanism. The MNAR mechanism is more strict and multiple imputation might not always work for missing data that is MNAR. However, when additional auxiliary variables are included in the missing data handling, to make the MAR assumption more plausible, multiple imputation can give valid analysis results. 

The missing data method should be applied to the total scores of the questionnaire directly. In this situation where the missing data are MNAR and no more than 50% of the subjects have missing data, multiple imputation can be performed (Eekhout et al. 2014). However, the percentage of subjects with missing values cannot be too large and auxiliary variables that might partly explain the missing data or correlate to the variables with missing data should be included in the imputation model.