Journal article
Categorical data regression diagnostics for remote access servers
Journal of statistical computation and simulation, Vol.75(11), pp.889-903
11/01/2005
DOI: 10.1080/00949650412331299184
Abstract
Owing to the growing concerns over data confidentiality, many national statistical agencies are considering remote access servers to disseminate data to the public. With remote servers, users submit requests for output from statistical models fit using the collected data, but they are not allowed access to the data. Remote servers also should enable users to check the fit of their models; however, standard diagnostics like residuals or influence statistics can disclose individual data values. In this article, we present diagnostics for categorical data regressions that can be safely and usefully employed in remote servers. We illustrate the diagnostics with simulation studies.
Details
- Title: Subtitle
- Categorical data regression diagnostics for remote access servers
- Creators
- Jerome P. Reiter - Duke UniversityChristine N. Kohnen - Duke University
- Resource Type
- Journal article
- Publication Details
- Journal of statistical computation and simulation, Vol.75(11), pp.889-903
- Publisher
- Taylor & Francis
- DOI
- 10.1080/00949650412331299184
- ISSN
- 0094-9655
- eISSN
- 1563-5163
- Number of pages
- 15
- Language
- English
- Date published
- 11/01/2005
- Academic Unit
- Biostatistics
- Record Identifier
- 9984721217502771
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