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The case for small area microdata

The case for small area microdata
The case for small area microdata
Census data are available in aggregate form for local areas and, through the samples of anonymized records (SARs), as samples of microdata for households and individuals. In 1991 there were two SAR files: a household file and an individual file. These have a high degree of detail on the census variables but little geographical detail, a situation that will be exacerbated for the 2001 SAR owing to the loss of district level geography on the individual SAR. The paper puts forward the case for an additional sample of microdata, also drawn from the census, that has much greater geographical detail. Small area microdata (SAM) are individual level records with local area identifiers and, to maintain confidentiality, reduced detail on the census variables. Population data from seven local authorities, including rural and urban areas, are used to define prototype samples of SAM. The rationale for SAM is given, with examples that demonstrate the role of local area information in the analysis of census data. Since there is a trade-off between the extent of local detail and the extent of detail on variables that can be made available, the confidentiality risk of SAM is assessed empirically. An indicative specification of the SAM is given, having taken into account the results of the confidentiality analysis.
census, data intrusion simulation, local area effects, multilevel models, population threshold, samples of anonymized records
0964-1998
29-49
Tranmer, M.
bcebe6d8-40c4-49ce-8f3a-0245f4bf7025
Pickles, A.
570e995c-1019-4da5-9bf3-0494caf42818
Fieldhouse, E.
778cd95e-006c-4525-994f-c2c446fab302
Elliot, M.
d26715eb-cf95-42e6-9a17-bb3446bb0af8
Dale, A.
c5fe67be-9783-4e0f-b299-8c3ffb96085f
Brown, M.
52cf4f52-6839-4658-8cc5-ec51da626049
Martin, D.
e5c52473-e9f0-4f09-b64c-fa32194b162f
Steel, D.
2b993cfb-2db9-4675-9ed0-2bbc549e52f1
Gardiner, C.
9677e97b-581a-4a2c-a3f8-c81833ccdaaa
Tranmer, M.
bcebe6d8-40c4-49ce-8f3a-0245f4bf7025
Pickles, A.
570e995c-1019-4da5-9bf3-0494caf42818
Fieldhouse, E.
778cd95e-006c-4525-994f-c2c446fab302
Elliot, M.
d26715eb-cf95-42e6-9a17-bb3446bb0af8
Dale, A.
c5fe67be-9783-4e0f-b299-8c3ffb96085f
Brown, M.
52cf4f52-6839-4658-8cc5-ec51da626049
Martin, D.
e5c52473-e9f0-4f09-b64c-fa32194b162f
Steel, D.
2b993cfb-2db9-4675-9ed0-2bbc549e52f1
Gardiner, C.
9677e97b-581a-4a2c-a3f8-c81833ccdaaa

Tranmer, M., Pickles, A., Fieldhouse, E., Elliot, M., Dale, A., Brown, M., Martin, D., Steel, D. and Gardiner, C. (2004) The case for small area microdata. Journal of the Royal Statistical Society: Series A (Statistics in Society), 168 (1), 29-49.

Record type: Article

Abstract

Census data are available in aggregate form for local areas and, through the samples of anonymized records (SARs), as samples of microdata for households and individuals. In 1991 there were two SAR files: a household file and an individual file. These have a high degree of detail on the census variables but little geographical detail, a situation that will be exacerbated for the 2001 SAR owing to the loss of district level geography on the individual SAR. The paper puts forward the case for an additional sample of microdata, also drawn from the census, that has much greater geographical detail. Small area microdata (SAM) are individual level records with local area identifiers and, to maintain confidentiality, reduced detail on the census variables. Population data from seven local authorities, including rural and urban areas, are used to define prototype samples of SAM. The rationale for SAM is given, with examples that demonstrate the role of local area information in the analysis of census data. Since there is a trade-off between the extent of local detail and the extent of detail on variables that can be made available, the confidentiality risk of SAM is assessed empirically. An indicative specification of the SAM is given, having taken into account the results of the confidentiality analysis.

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More information

Published date: 15 December 2004
Keywords: census, data intrusion simulation, local area effects, multilevel models, population threshold, samples of anonymized records
Organisations: PHEW – S (Spatial analysis and modelling), Remote Sensing & Spatial Analysis

Identifiers

Local EPrints ID: 55759
URI: https://eprints.soton.ac.uk/id/eprint/55759
ISSN: 0964-1998
PURE UUID: f23ec093-9144-4927-a29d-a97a713bf94c
ORCID for D. Martin: ORCID iD orcid.org/0000-0003-0397-0769

Catalogue record

Date deposited: 26 Aug 2008
Last modified: 06 Jun 2018 13:09

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Contributors

Author: M. Tranmer
Author: A. Pickles
Author: E. Fieldhouse
Author: M. Elliot
Author: A. Dale
Author: M. Brown
Author: D. Martin ORCID iD
Author: D. Steel
Author: C. Gardiner

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