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Principles and Practices for a Federal Statistical Agency Sixth Edition (2017) / Chapter Skim
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Practice 12: A Strong Internal and External Evaluation Program
Pages 113-116

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From page 113...
... will likely be in a good position to make continuous assessments of and improvements in the relevance, quality, and efficiency of their data collection systems. Yet even the best 87 OMB issued a proposed addendum, Section 10: Performance Review, to Statistical Policy Directive No.
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From page 114...
... Regular, welldesigned program evaluations, with adequate budget support, are key to ensuring that data collection programs do not deteriorate. Having a set schedule for research and development efforts will enable data collection managers to ensure that the quality and usefulness of their data are maintained and help prevent that increasingly less optimal procedures are locked in over time.
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From page 115...
... For this purpose, statistical agencies should develop complete, informative models for evaluating costs of current procedures and possible alternatives and follow best practice for design of statistical production processes. One excellent guide to best practices is the Generic Statistical Business Process Model of the United Nations Economic Commission for Europe.
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From page 116...
... Independent external evaluations should also be conducted on a regular basis, the frequency of which should depend on the importance of the data, how quickly the phenomena being measured change, and how quickly respondent behavior and data collection technology that may adversely affect a program change. In a world in which people and organizations are increasingly less willing to respond to surveys, it becomes increasingly urgent to have more frequent evaluations to determine whether there are alternative data sources to surveys with better quality.
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  • program priorities
  • includes unit
  • professional standards
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  • entire portfolio
  • desired characteristics
  • adequate budget
  • properly called
  • statistical units

  • collection technology
  • external evaluation
  • program evaluations
  • reduce respondent
  • improve data


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