Handbook on Precision Requirements and Variance Estimation for ESS Household Surveys
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Transcript of Handbook on Precision Requirements and Variance Estimation for ESS Household Surveys
Handbook on Precision Requirements and Variance Estimation for ESS Household Surveys
Denisa Florescu, Eurostat
European Conference on Quality in Official StatisticsVienna, 3-5 June 2014
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Contents
1. Standard formulation of precision requirements
2. Variance estimation methods and tools Good and bad practices
3. Approaches to compute standard errors for national and EU statistics
4. Guidance to assess the compliance to the requirements
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Standard formulation of precision requirements
Two strategies
Precision thresholds to be met by a few main target national indicators
Minimum effective sample sizes to be ensured by National Statistical Institutes
• Quality of the output
• Recommended for regulations
• They ensure satisfactory precision for a few indicators, too
• Design requirements, not quality of the output
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Standard formulation of precision requirements
Precision measures geared to the type of statistics
Relative precision measures Absolute precision measures
recommended for:
• Totals and means of continuous variables
• Proportions
• Ratios and changes close to 0
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Impact of proportion on the minimum sample size needed to achieve a coefficient of variation of 5 %,
under simple random sampling
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
estimated proportion
Sample size
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Standard formulation of precision requirements
For EU regulations, for:
proportions
overall national estimates and estimates of national breakdowns
estimates of level and net changes of estimates of level
Some versions e.g. precision expressed as model function of estimated proportions
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Evaluation of methods and recommendations using various criteria e.g.:
Applicability to sampling designs and types of statistics: choice guided by a
developed matrix:
Types of statistics
Sampling designs
Linear Ratios Non-linear, smooth
Non-smooth
… … … … …
… … … … …
• Suitable methods
• Unsuitable methods
• References
Variance estimation methods
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Type of data Approach Methods
Aggregated Decentralised in NSIs Various
Integratedburden shared by NSIs and Eurostat
Generalised variance functionsparameters provided by NSIs
Approaches to compute standard errors for national and European statistics
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Type of data Approach Methods
Microdata Integratedburden shared by NSIs and Eurostat
Replication methods
Fully centralized
burden in Eurostat
Replication methods
Approaches to compute standard errors for national and European statistics
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Guidance to assess compliance to requirements
Principles of transparency and tolerance
3 strategies:
Use of integrated or fully centralised approach in Eurostat
Trace systematic deviations on the basis of quality reports (metadata template proposed)
Fixed normative rules agreed in advance between NSIs and Eurostat