Imputation of missing item responses: Some simple techniques

Among the wide variety of procedures to handle missing data, imputing the missing values is a popular strategy to deal with missing item responses. In this paper some simple and easily implemented imputation techniques like item and person mean substitution, and some hot-deck procedures, are investigated. A simulation study was performed based on responses to items forming a scale to measure a latent trait of the respondents. The effects of different imputation procedures on the estimation of the latent ability of the respondents were investigated, as well as the effect on the estimation of Cronbach's alpha (indicating the reliability of the test) and Loevinger's H-coefficient (indicating scalability). The results indicate that procedures which use the relationships between items perform best, although they tend to overestimate the scale quality.