Missing Data in Likert Ratings: A Comparison of Replacement Methods

Abstract The effects of using two methods (item mean and person mean) for replacing missing data in Likert scales were studied. The results showed that both methods were good representations of the original data when both the number of respondents with missing data and the number of items missing were 20% or less. As the numbers of missing items and of respondents with missing data increased for the person mean substitution method, a spurious increase in the inter-item correlations (and, therefore, reliability) for the scale was produced. The item mean substitution reduced the reliability estimates of the scale. These results suggest caution in the use of the person mean substitution method as the numbers of missing items and respondents increase.