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S T A T I S T I K A U S T R I A14.4.2010 1
www.statistik.at
Quality Assessment of register-based StatisticsA Quality Framework
Manuela LENK
Directorate Population Statistics
Register based census© STATISTIK AUSTRIA
I n f o r m a t i o n e n
Wir bewegen
S T A T I S T I K A U S T R I A14.4.2010 2
Switch from traditional to register-based census in Austria 2011 Compared to other countries transition time is relatively short Census Test was carried out for 2006
Seven base registers and several comparision registers Registers are combined using unique identifiers (bPK) Gathering experience for the register-based census
Introduction
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S T A T I S T I K A U S T R I A14.4.2010 3
Quality is influenced by (according to the quality report as requested by Eurostat)
Quality of the administrative data source Existence of an unique key or rather the availability to
link a person Comparision between survey and administrative data Item imputation
Consequence Establishing a quality framework for the register based
census 2011 – cooperation with WU Vienna
Quality Issues in Census Test
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S T A T I S T I K A U S T R I A14.4.2010 4
Quality assessment of statistics based on administrative data Quality Indicator for
Raw Data – data obtained from administrative sources Each attribute in each register Whole register (data source)
Census 2011 Attributes of the Final Data Pool
Objectives
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S T A T I S T I K A U S T R I A14.4.2010 5
Assessment of quality is derived from hyperdimensions (HD) for each attribute in each register.
Documentation Pre-Processing External Sources Imputation
Hyperdimensions
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S T A T I S T I K A U S T R I A14.4.2010 6
Documentation Focus is on processes taking place before the data is transfered to
Statistics Austria Data treatment at the source maintaining the register Reliability of the data source
Quality criteria Relevance of attributes for the source (e.g. legal foundation) Availability for certain reference dates Compatible definitons
Registers are benchmarked using a perfect pseudo register Informations are extracted from the meta database
Hyperdimensions (1)
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S T A T I S T I K A U S T R I A14.4.2010 7
Pre-Processing Process of Data editing from Raw Data to the Edited Data Analysis of Raw Data
Error corrections Recoding Plausibility checks
Quality criteria Proportion of missing unique keys Proportion of values out of domain Item non-response
Automated generation out of database
Hyperdimensions (2)
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External Source Checks accuracy of the data record linkage with survey data (e.g. Labour Force Survey)
Quality criteria Consistency of attribute values
For some attributes no external source for comparision exists, thus it is being replaced by
Expert interviews Rating of accuracy – expert knowledge obtained from working
experience Subjective – should be considered when allocating the weight for
this hyperdimension
Hyperdimensions (3)
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Each hyperdimension receives a weight in accordance with its relevance for the project.
Within these hyperdimensions quality criteria are determined and quality indicators are derived for each hyperdimension (HDD, HDP, HDE).
After weighting these dimensions (vD, vP, vE) we get an aggregated quality indicator q.
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Quality Indicators (1)
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S T A T I S T I K A U S T R I A14.4.2010 10
Finally we are able to derive a quality indicator qij for each attribute in each register
We could derive an aggregated quality indicator for each register too (weighted row sum).
Quality Indicators (2)
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S T A T I S T I K A U S T R I A14.4.2010 11
Register-based census Quality assessment within the Census Database
Combination of existing registers to a new data base.
Quality assessment of the Final Data Pool Census Database including item imputations.
Application on linked data sets
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S T A T I S T I K A U S T R I A14.4.2010 12
Unique Attributes attribute exists exactly once in one register and is transfered directly to the CD
qij = qj = qΨj link
Multiple Attributes attribute exists in more than one register. Information from different sources are combined in the CD using certain decision rules – e.g. majority principle (Sex)
Quality indicators for this attribute from different registers are combined to an overall quality indicator qj (e.g Dempster-Shafer Theory)
Additional check using external data source HDE leads to a corrected quality indicator qΨj link
Derived Attributes several attributes are linked to a new attribute Quality indicator qj is generated by using the quality indicators of the
input attributes Additional check using external data source HDE leads to a corrected
quality indicator qΨj link
Assessment of the Census Database (CD)
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S T A T I S T I K A U S T R I A14.4.2010 13
Census Database including item imputations Hyperdimension Imputation (HDI)
Quality indicators depend on methods of imputation Shall be generated with appropriate valuation
methods The weight for this hyperdimension is approximated by
the proportion of imputation
Quality assessment of the Final Data Pool
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Process-oriented Quality Framework back
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Conclusion
Framework should act as a road map Next milestones are
Establishing check lists (questionnaires) Specify how to derive the quality indicators for each
hyperdimension and how to aggregate them
General approach Application to other projects is possible
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S T A T I S T I K A U S T R I A14.4.2010 16
Additional Information Quality Framework Fiedler/Schwerer/Berka/Humer/Moser: Quality Assessment for Register
based Statistics in Austria Register-based Census
www.statistik.at
Outlook
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