| Abstract [eng] |
In this work, we examined some missing data imputation methods in the survey on outbound tourism for the package tour and transport expenses. We performed an analysis of the efficiency of missing data imputation methods using full data sets with fictitious missing data applying various missing data imputation methods to fill in the missing data. Thus, we had real values and imputed values and could compare the estimated parameters. The missing data can appear randomly and non-randomly, so we applied missing data imputation methods in three cases: when missing data appear randomly and when missing data appear in case of non-response of respondents who had the highest or the lowest travel expenses. We applied distribution, average, random, ratio and multiple imputation methods for missing data imputation without using imputation classes and using imputation classes. We propose to perform the same efficiency survey of missing data imputation methods for the remaining items of expenses in the outbound tourism questionnaire in order to find out a convenient missing data imputation method and apply it for the real missing data (the current analysis was performed applying fictitious missing data). After the missing data imputation, we can apply the procedures of parameter estimation and we will not lose other information as it would be the case with the elimination of questionnaires having missing data. |
