Measurement error and statistical disclosure control

Natalie Shlomo

doi:10.1007/978-3-642-15838-4_11

Measurement error and statistical disclosure control

Natalie Shlomo

Social Statistics

Research output: Chapter in Book/Conference proceeding › Chapter

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. © 2010 Springer-Verlag Berlin Heidelberg.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\|Lect. Notes Comput. Sci.
Subtitle of host publication	Eds. J. Domingo-Ferrer and E. Magkos
Place of Publication	Germany
Publisher	Springer Nature
Pages	118-126
Number of pages	8
Volume	6344
DOIs	https://doi.org/10.1007/978-3-642-15838-4_11
Publication status	Published - 2010
Event	International Conference on Privacy in Statistical Databases, PSD 2010 - Corfu Duration: 1 Jul 2010 → …

Conference

Conference	International Conference on Privacy in Statistical Databases, PSD 2010
City	Corfu
Period	1/07/10 → …

Keywords

Additive noise
Post-randomisation method
Reliability ratio

Access to Document

10.1007/978-3-642-15838-4_11

Cite this

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title = "Measurement error and statistical disclosure control",

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. {\textcopyright} 2010 Springer-Verlag Berlin Heidelberg.",

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author = "Natalie Shlomo",

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note = "International Conference on Privacy in Statistical Databases, PSD 2010 ; Conference date: 01-07-2010",

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Shlomo, N 2010, Measurement error and statistical disclosure control. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.: Eds. J. Domingo-Ferrer and E. Magkos. vol. 6344, Springer Nature, Germany, pp. 118-126, International Conference on Privacy in Statistical Databases, PSD 2010, Corfu, 1/07/10. https://doi.org/10.1007/978-3-642-15838-4_11

Measurement error and statistical disclosure control. / Shlomo, Natalie.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.: Eds. J. Domingo-Ferrer and E. Magkos. Vol. 6344 Germany: Springer Nature, 2010. p. 118-126.

Research output: Chapter in Book/Conference proceeding › Chapter

TY - CHAP

T1 - Measurement error and statistical disclosure control

AU - Shlomo, Natalie

PY - 2010

Y1 - 2010

N2 - 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. © 2010 Springer-Verlag Berlin Heidelberg.

AB - 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. © 2010 Springer-Verlag Berlin Heidelberg.

KW - Additive noise

KW - Post-randomisation method

KW - Reliability ratio

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DO - 10.1007/978-3-642-15838-4_11

M3 - Chapter

VL - 6344

SP - 118

EP - 126

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.

PB - Springer Nature

CY - Germany

T2 - International Conference on Privacy in Statistical Databases, PSD 2010

Y2 - 1 July 2010

ER -

Measurement error and statistical disclosure control

Abstract

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Keywords

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