Data, Statistics, and Controversy: Making Science Research Data Intelligible
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Nell Sedransk
Making published, scientific research data publicly available can benefit scientists and policy makers only if there is sufficient information for these data to be intelligible. Thus the necessary meta-data go beyond the scientific, technological detail and extend to the statistical approach and methodologies applied to these data. The statistical principles that give integrity to researchers’ analyses and interpretations of their data require documentation. This is true when the intent is to verify or validate the published research findings; it is equally true when the intent is to utilize the scientific data in conjunction with other data or new experimental data to explore complex questions; and it is profoundly important when the scientific results and interpretations are taken outside the world of science to establish a basis for policy, for legal precedent or for decision-making. When research draws on already public data bases, e.g., a large federal statistical data base or a large scientific data base, selection of data for analysis, whether by selection (subsampling) or by aggregating, is specific to that research so that this (statistical) methodology is a crucial part of the meta-data. Examples illustrate the role of statistical meta-data in the use and reuse of these public datasets and the impact on public policy and precedent.
©2012 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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- Problems with Tests of the Missingness Mechanism in Quantitative Policy Studies
- Climate Statistics and Public Policy
- Commentary and Ideas
- Data, Statistics, and Controversy: Making Science Research Data Intelligible
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- Why and When "Flawed" Social Network Analyses Still Yield Valid Tests of no Contagion
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Artikel in diesem Heft
- Article
- Improving Statistical Inference with Clustered Data
- Major Contributions to Quantitative Economics Sponsored by the Defense Community
- Problems with Tests of the Missingness Mechanism in Quantitative Policy Studies
- Climate Statistics and Public Policy
- Commentary and Ideas
- Data, Statistics, and Controversy: Making Science Research Data Intelligible
- Response or Comment
- Why and When "Flawed" Social Network Analyses Still Yield Valid Tests of no Contagion
- Comment on "Why and When 'Flawed' Social Network Analyses Still Yield Valid Tests of no Contagion"
