z-logo
open-access-imgOpen Access
Constructing a toolkit to evaluate quality of state and local administrative data
Author(s) -
Zachary H. Seeskin,
Gabriel Ugarte,
A. Rupa Datta
Publication year - 2019
Publication title -
international journal of population data science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.602
H-Index - 7
ISSN - 2399-4908
DOI - 10.23889/ijpds.v4i1.937
Subject(s) - comparability , computer science , data quality , exploit , quality (philosophy) , data science , state (computer science) , resource (disambiguation) , data mining , computer security , engineering , operations management , computer network , metric (unit) , philosophy , mathematics , algorithm , epistemology , combinatorics
In the United States, state and local agencies administering government assistance programs have in their administrative data a powerful resource for policy analysis to inform evaluation and guide improvement of their programs. Understanding different aspects of their administrative data quality is critical for agencies to conduct such analyses and to improve their data for future use. However, state and local agencies often lack the resources and training for staff to conduct rigorous evaluations of data quality. We describe our efforts in developing tools that can be used to assess data quality as well as the challenges encountered in constructing these tools. The toolkit focuses on critical dimensions of quality for analyzing an administrative dataset, including checks on data accuracy, the completeness of the records, and the comparability of the data over time and among subgroups of interest. State and local administrative databases often include a longitudinal component which our toolkit also aims to exploit to help evaluate data quality. In addition, we incorporate data visualization to draw attention to sets of records or variables that contain outliers or for which quality may be a concern. While we seek to develop general tools for common data quality analyses, most administrative datasets have particularities that can benefit from a customized analysis building on our toolkit.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here