Data cleaning, or data cleansing, is an important part of the process involved in preparing data for analysis. Data cleaning is a subset of data preparation, which also includes scoring tests, matching data files, selecting cases, and other tasks that are required to prepare data for analysis.
Missing and erroneous data can pose a significant problem to the reliability and validity of study outcomes. Many problems can be avoided through careful survey and study design. During the study, watchful monitoring and data cleaning can catch problems while they can still be fixed. At the end of the study, multiple imputation procedures may be used for data that are truly irretrievable.
The opportunities for data cleaning are dependent on the study design and data collection methods. At one ...
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