Measurement error and statistical disclosure control
Measurement error and statistical disclosure control
Statistical agencies release microdata to researchers after applying statistical disclosure control (SDC) methods. Noise addition is a perturbative SDC method which is carried out by adding independent random noise to a continuous variable or by misclassifying values of a categorical variable according to a probability mechanism. Because these errors are purposely introduced into the data by the statistical agency, the perturbation parameters are known and can be used by researchers to adjust statistical inference through measurement error models. However, statistical agencies rarely release perturbation parameters and therefore modifications to SDC methods are proposed that a priori ensure valid inferences on perturbed datasets.
Additive noise, post-randomisation method, reliability ratio
Southampton Statistical Sciences Research Institute, University of Southampton
Shlomo, Natalie
e749febc-b7b9-4017-be48-96d59dd03215
16 July 2010
Shlomo, Natalie
e749febc-b7b9-4017-be48-96d59dd03215
Shlomo, Natalie
(2010)
Measurement error and statistical disclosure control
(S3RI Methodology Working Papers, M10/05)
Southampton, GB.
Southampton Statistical Sciences Research Institute, University of Southampton
Record type:
Monograph
(Working Paper)
Abstract
Statistical agencies release microdata to researchers after applying statistical disclosure control (SDC) methods. Noise addition is a perturbative SDC method which is carried out by adding independent random noise to a continuous variable or by misclassifying values of a categorical variable according to a probability mechanism. Because these errors are purposely introduced into the data by the statistical agency, the perturbation parameters are known and can be used by researchers to adjust statistical inference through measurement error models. However, statistical agencies rarely release perturbation parameters and therefore modifications to SDC methods are proposed that a priori ensure valid inferences on perturbed datasets.
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s3ri-workingpaper-M10-05.pdf
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Published date: 16 July 2010
Keywords:
Additive noise, post-randomisation method, reliability ratio
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Local EPrints ID: 160659
URI: http://eprints.soton.ac.uk/id/eprint/160659
PURE UUID: 887ac111-2fc8-4b6f-b5db-f00cf0913ce1
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Date deposited: 16 Jul 2010 10:20
Last modified: 06 Oct 2020 23:12
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Author:
Natalie Shlomo
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