<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Many national statistics offices acknowledge that making better use of existing administrative data can reduce the cost of meeting ongoing statistical needs. Stats NZ has developed a framework to help facilitate this reuse. The framework is an adapted Total Survey Error (TSE) paradigm for understanding how the strengths and limitations of different data sets flow through a statistical design to affect final output quality. Our framework includes three phases: 1) a single source assessment, 2) an integrated data set assessment, and 3) an estimation and output assessment. We developed a process and guidelines for applying this conceptual framework to practical decisions about statistical design, and used these in recent redevelopment projects. We discuss how we used the framework with data sources that have a non-statistical primary purpose, and how it has helped us spread total survey error ideas to non-methodologists.</p></abstract>

Many national statistics offices acknowledge that making better use of existing administrative data can reduce the cost of meeting ongoing statistical needs. Stats NZ has developed a framework to help facilitate this reuse. The framework is an adapted Total Survey Error (TSE) paradigm for understanding how the strengths and limitations of different data sets flow through a statistical design to affect final output quality. Our framework includes three phases: 1) a single source assessment, 2) an integrated data set assessment, and 3) an estimation and output assessment. We developed a process and guidelines for applying this conceptual framework to practical decisions about statistical design, and used these in recent redevelopment projects. We discuss how we used the framework with data sources that have a non-statistical primary purpose, and how it has helped us spread total survey error ideas to non-methodologists.

Extending TSE to Administrative Data: A Quality Framework and Case Studies from Stats NZ

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Many national statistics offices acknowledge that making better use of existing administrative data can reduce the cost of meeting ongoing statistical needs....

Extending TSE to Administrative Data: A Quality Framework and Case Studies from Stats NZ

Online veröffentlicht: 12. Juni 2017

Seitenbereich: 477 - 511

Eingereicht: 01. Jan. 2016

Akzeptiert: 01. März 2017

DOI: https://doi.org/10.1515/jos-2017-0023

Schlüsselwörter
Total survey error, multiple data sources, official statistics, survey design

© 2017 Giles Reid et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Extending TSE to Administrative Data: A Quality Framework and Case Studies from Stats NZ

Online veröffentlicht: 12. Juni 2017

Seitenbereich: 477 - 511

Eingereicht: 01. Jan. 2016

Akzeptiert: 01. März 2017

DOI: https://doi.org/10.1515/jos-2017-0023

SchlüsselwörterTotal survey error, multiple data sources, official statistics, survey design

© 2017 Giles Reid et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Total survey error, multiple data sources, official statistics, survey design