Accuracy - Quality Statement
The degree to which the data correctly describe the phenomenon they were designed to measure. This is an important component of quality as it relates to how well the data portray reality, which has clear implications for how useful and meaningful the data will be for interpretation or further analysis. In particular, when using administrative data, it is important to remember that statistical outputs for analysis are generally not the primary reason for the collection of the data.
Accuracy should be assessed in terms of the major sources of errors that potentially cause inaccuracy. Any factors which could impact on the overall validity of the information for users should be described in quality statements. Aspects of accuracy which should be addressed, where appropriate, include:
- the role of data providers and AIHW in ensuring quality
- coverage error: this occurs when a unit in the data is incorrectly excluded or included, or is duplicated in the data
- response error: this refers to a type of error caused by records being intentionally or accidentally inaccurate or incomplete. This occurs not only in statistical surveys, but also in administrative data collection where forms, or concepts on forms, are not well understood by respondents
- non-response error: this refers to incomplete information for a record (e.g., when some data are missing). The use of any imputation strategies should be noted
- sample error: where sampling is used, the impact of sample error can be assessed using information about the sample design, the total sample size and the size of the sample in key output levels. For sample surveys, response rates should be provided
- other sources of errors: Any other serious accuracy problems with the statistics should be considered. These may include errors caused by incorrect processing of data (e.g. erroneous data entry or recognition), rounding errors involved during collection, processing or dissemination, and other quality assurance processes
- the quality of indigenous status data should be noted, especially when they are only of sufficient quality for statistical reporting purposes for selected jurisdictions
- revisions to data: the extent to which the data are subject to revision or correction, in light of new information or following rectification of errors in processing or estimation, and the time frame in which revisions are produced