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1. Agriculture–Population Linkage: Data quality report
Surveys and statistical programs – Documentation: 32-26-0006
Description: This report provides data quality information pertaining to the Agriculture–Population Linkage, such as sources of error, matching process, response rates, imputation rates, sampling, weighting, disclosure control methods and data quality indicators.
Release date: 2023-08-25
2. Quality-preserving controlled tabular adjustment: a method for resolving confidentiality and data quality issues for tabular data Archived
Articles and reports: 11-522-X20050019434
Description:
Traditional methods for statistical disclosure limitation in tabular data are cell suppression, data rounding and data perturbation. Because the suppression mechanism is not describable in probabilistic terms, suppressed tables are not amenable to statistical methods such as imputation. Data quality characteristics of suppressed tables are consequently poor.
Release date: 2007-03-02
3. Common metadata constructs for statistical data Archived
Articles and reports: 11-522-X20050019436
Description:
Regardless of the specifics of any given metadata scheme, there are common metadata constructs used to describe statistical data. This paper will give an overview of the different approaches taken to achieve the common goal of providing consistent information.
Release date: 2007-03-02
4. Variance information for data users Archived
Articles and reports: 11-522-X20050019462
Description:
The traditional approach to presenting variance information to data users is to publish estimates of variance or related statistics, such as standard errors, coefficients of variation, confidence limits or simple grading systems. The paper examines potential sources of variance, such as sample design, sample allocation, sample selection, non-response, and considers what might best be done to reduce variance. Finally, the paper assesses briefly the financial costs to producers and users of reducing or not reducing variance and how we might trade off the costs of producing more accurate statistics against the financial benefits of greater accuracy.
Release date: 2007-03-02

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1. Quality-preserving controlled tabular adjustment: a method for resolving confidentiality and data quality issues for tabular data Archived
Articles and reports: 11-522-X20050019434
Description:
Traditional methods for statistical disclosure limitation in tabular data are cell suppression, data rounding and data perturbation. Because the suppression mechanism is not describable in probabilistic terms, suppressed tables are not amenable to statistical methods such as imputation. Data quality characteristics of suppressed tables are consequently poor.
Release date: 2007-03-02
2. Common metadata constructs for statistical data Archived
Articles and reports: 11-522-X20050019436
Description:
Regardless of the specifics of any given metadata scheme, there are common metadata constructs used to describe statistical data. This paper will give an overview of the different approaches taken to achieve the common goal of providing consistent information.
Release date: 2007-03-02
3. Variance information for data users Archived
Articles and reports: 11-522-X20050019462
Description:
The traditional approach to presenting variance information to data users is to publish estimates of variance or related statistics, such as standard errors, coefficients of variation, confidence limits or simple grading systems. The paper examines potential sources of variance, such as sample design, sample allocation, sample selection, non-response, and considers what might best be done to reduce variance. Finally, the paper assesses briefly the financial costs to producers and users of reducing or not reducing variance and how we might trade off the costs of producing more accurate statistics against the financial benefits of greater accuracy.
Release date: 2007-03-02

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1. Agriculture–Population Linkage: Data quality report
Surveys and statistical programs – Documentation: 32-26-0006
Description: This report provides data quality information pertaining to the Agriculture–Population Linkage, such as sources of error, matching process, response rates, imputation rates, sampling, weighting, disclosure control methods and data quality indicators.
Release date: 2023-08-25

Date modified:: 2026-08-13