The presence of non-response for some items on a scale of measurement is a phenomenon which any researcher is suitable to meet during his work. Despite the extent of this problem, knowledge about bias or effectiveness of the missing data treatment is still very restricted. The aim of the present study is to evolve knowledge and practices concerning the treatment of the missing values in the context of Likert-type scales. This research project, based on a Monte Carlo methodology, compares the effectiveness of five methods of treatment. The multiple imputation, the method which is in the process of becoming the standard, is shown as being one of the most effective methods of treatment, minimizing the presence of bias as much on the level of the coefficient alpha of Cronbach that on the scale score.