Data processing and imputation methods
Data editing and validation
The stage of processing and analysis of the collected data includes data editing, imputation, estimation, integration and analysis. Editing data, simply put, means checking data to detect errors. Firstly, data completeness is checked – whether for all observations we obtained answers to all the questions asked. Then, data validation can be performed, i.e. determining whether the responses collected are possible/acceptable, and for this purpose, for example, the ranges of acceptable data are used. We further examine if there are acceptable relationships between the data by checking the proportions between variables and the correctness of arithmetic calculations, such as adding variables to the total sum.
Methods for imputing missing data
We distinguish 2 types of missing values – they may concern the lack of answer from a surveyed unit (unit non-response) or lack of answer to individual questions (item non-response). In the first case, we deal with this problem by using data weighting methods, while in the second case, we use data imputation methods. Imputation is completing missing data. There are many methods of imputation.
When using imputation, one should bear in mind that the assigned values are only artificially introduced substitutes for the answers.