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From page 26... ...
Statistical agencies have also developed requirements for their internal use to support transparency. An example is the Census Bureau Statistical Quality Standards,12 which contains the following requirements, as summarized in Table 1-2.
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. Survey documentation must be readily accessible to users unless it is necessary to restrict access to protect confidentiality.
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. Public-use microdata documentation and metadata must be readily accessible to users.
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Guideline 7.4.6: Retain all microdata products and documentation according to appropriate Federal records disposition and archival policy. Archive data with the National Archives and Records Administration and other data archives, as appropriate, so that data are available for historical research in future years.
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For example, the release of some input datasets from surveys could make confidential personal information for individuals or businesses available, which would violate the law as well as undermine trust in the statistical agency. Further, because statistical agencies are increasingly relying on nonsurvey data, including administrative, commercial, and other digital trace data, the data may come with additional restrictions on transparency.
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Chapter 4 discusses changes in documentation practices that could facilitate transparency and reproducibility of the statistical methods used in the federal statistical agencies. These includes various information technol ogy tools to assist with version control and software development, as well as collaboration tools and methods for retaining workflows.
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Finally, Chapter 7 provides a discussion of best practices for federal statistical agencies. This chapter lays out aspects of what a more modern approach to federal statistics would consist of, including better documentation and archiving practices that provide for data and methodology sharing among agencies and a smoother interface with the public.
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, an estimation methodology, and whatever validation is used to assess the quality of the resulting official statistics. If estimates instead use data from administrative records or digital trace data,1 other technical questions may have to be dealt with.
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There is also use of imputation employed for item nonresponse. Many users of official statistics have an incomplete understanding not only of the complexity of the collection of the raw input data, but of the measures taken to turn those input data into the final official estimates.
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Know ing how a set of official statistics is produced entails retaining details of the various data collection processes used, including the survey design, the survey instruments and field instructions, should survey data be collected, or retaining descriptions of any processes used to collect data from admin istrative sources and/or from digital traces. Then, whatever computations are carried out in converting the raw input data to the set of inputs fed into the estimation methodology also need to be documented.
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In addition, as part of such detailed documentation, when changes are made it is important not only to make the associated changes in the documentation, but to make available an explanation as to why the changes needed to be made. The precise location of the changes in the software code, either for the workflow history of the data treatments or for estimations, also needs to be made available, depending on what has changed.
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These improvements and innovations can arise either within an agency or through the external research community, and therefore both internal staff and external researchers need to be aware of the current approaches used for the production of a set of official statistics so that they can assess when a new idea might provide an improvement over the status quo. Trust and Confidence If statistical agencies wish the public to trust the estimates coming from the government, they should recognize that it is important to demonstrate to the public that the techniques used for data collection and the methods used on the collected data are not used to benefit any stakeholders and that they represent the current state of the art.
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From page 38... ...
These standards say much less about statistical programs that are based on administrative data or digital trace data. Similarly, OMB provides less guidance with respect to the documentation of methodologies either used for data treatment or for estimation associated with the official statistics, including whether the associated software code should be made known to the public.
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