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All (15) (0 to 10 of 15 results)

  • Articles and reports: 46-28-0001202200100001
    Description:

    When a survey publishes statistics with a quality indicator, it is usually derived from measures based on sampling theory. The production of quality indicators is a significant challenge when statistics are produced using alternative sources for which no sampling is done. This paper describes a new method used to create a quality indicator that combines indicators obtained at different stages of data processing. An example of the application of the method in the Canadian Housing Statistics Program is provided in the Appendix.

    Release date: 2022-01-06

  • Articles and reports: 11-522-X202100100015
    Description: National statistical agencies such as Statistics Canada have a responsibility to convey the quality of statistical information to users. The methods traditionally used to do this are based on measures of sampling error. As a result, they are not adapted to the estimates produced using administrative data, for which the main sources of error are not due to sampling. A more suitable approach to reporting the quality of estimates presented in a multidimensional table is described in this paper. Quality indicators were derived for various post-acquisition processing steps, such as linkage, geocoding and imputation, by estimation domain. A clustering algorithm was then used to combine domains with similar quality levels for a given estimate. Ratings to inform users of the relative quality of estimates across domains were assigned to the groups created. This indicator, called the composite quality indicator (CQI), was developed and experimented with in the Canadian Housing Statistics Program (CHSP), which aims to produce official statistics on the residential housing sector in Canada using multiple administrative data sources.

    Keywords: Unsupervised machine learning, quality assurance, administrative data, data integration, clustering.

    Release date: 2021-10-22

  • Articles and reports: 11F0019M2019025
    Description:

    This study identifies gig workers based on characteristics of their work arrangements and how these are reported in tax data. It introduces a definition of gig work specific to the way work arrangements are reported in the Canadian tax system and estimates the size of the gig economy in Canada using administrative data. The share of gig workers among all workers rose from 5.5% in 2005 to 8.2% in 2016. Some of this increase coincided with the introduction and proliferation of online platforms. The analysis highlights gender differences in the trends and characteristics of gig workers. By linking administrative data to 2016 Census microdata, this study also examines educational and occupational differences in the prevalence of gig workers.

    Release date: 2019-12-16

  • Articles and reports: 75F0002M2019007
    Description:

    Not having a Social Insurance Number (SIN) and not filing taxes may represent challenges to access government programs and supports such as the Canada Education Savings Grant (CESG) and the Canada Learning Bond (CLB). Limited data availability has prevented a full assessment of the extent of these access challenges. This study attempts to address this knowledge gap by analyzing overall differences in SIN possession and tax-filing uptake by family income, levels of parental education, family type and Indigenous identity of the child and age of children using the 2016 Census data augmented with tax-filing and Social Insurance Number possession indicator flags.

    Release date: 2019-06-21

  • Articles and reports: 11-633-X2018013
    Description:

    Since 2008, a number of population censuses have been linked to administrative health data and to financial data. These linked datasets have been instrumental in examining health inequalities and have been used in environmental health research. This paper describes the creation of the 1996 Canadian Census Health and Environment Cohort (CanCHEC)—3.57 million respondents to the census long-form questionnaire who were retrospectively followed for mortality and mobility for 16.6 years from 1996 to 2012. The 1996 CanCHEC was limited to census respondents who were aged 19 or older on Census Day (May 14, 1996), were residents of Canada, were not residents of institutions, and had filed an income tax return. These respondents were linked to death records from the Canadian Mortality Database or to the T1 Personal Master File, and to a postal code history from a variety of sources. This is the third in a set of CanCHECs that, when combined, make it possible to examine mortality trends and environmental exposures by socioeconomic characteristics over three census cycles and 21 years of census, tax, and mortality data. This report describes linkage methodologies, validation and bias assessment, and the characteristics of the 1996 CanCHEC. Representativeness of the 1996 CanCHEC relative to the adult population of Canada is also assessed.

    Release date: 2018-01-22

  • Articles and reports: 11-522-X201700014715
    Description:

    In preparation for 2021 UK Census the ONS has committed to an extensive research programme exploring how linked administrative data can be used to support conventional statistical processes. Item-level edit and imputation (E&I) will play an important role in adjusting the 2021 Census database. However, uncertainty associated with the accuracy and quality of available administrative data renders the efficacy of an integrated census-administrative data approach to E&I unclear. Current constraints that dictate an anonymised ‘hash-key’ approach to record linkage to ensure confidentiality add to that uncertainty. Here, we provide preliminary results from a simulation study comparing the predictive and distributional accuracy of the conventional E&I strategy implemented in CANCEIS for the 2011 UK Census to that of an integrated approach using synthetic administrative data with systematically increasing error as auxiliary information. In this initial phase of research we focus on imputing single year of age. The aim of the study is to gain insight into whether auxiliary information from admin data can improve imputation estimates and where the different strategies fall on a continuum of accuracy.

    Release date: 2016-03-24

  • Surveys and statistical programs – Documentation: 75-005-M2015001
    Description:

    Using the experimental Workplace Survey conducted in 2011, this technical document summarizes the main results and evaluates the quality of the data.

    Release date: 2015-04-28

  • Articles and reports: 82-003-X201500214140
    Description:

    This study examines the feasibility and limitations of applying a non-categorical approach (focused on service utilization rather than on specific diagnoses) to administrative data in order to identify children with health problems.

    Release date: 2015-02-18

  • Articles and reports: 11-522-X201300014284
    Description:

    The decline in response rates observed by several national statistical institutes, their desire to limit response burden and the significant budget pressures they face support greater use of administrative data to produce statistical information. The administrative data sources they must consider have to be evaluated according to several aspects to determine their fitness for use. Statistics Canada recently developed a process to evaluate administrative data sources for use as inputs to the statistical information production process. This evaluation is conducted in two phases. The initial phase requires access only to the metadata associated with the administrative data considered, whereas the second phase uses a version of data that can be evaluated. This article outlines the evaluation process and tool.

    Release date: 2014-10-31

  • Articles and reports: 82-003-X201300111764
    Geography: Province or territory
    Description:

    This study compares two sources of information about prescription drug use by people aged 65 or older in Ontario - the Canadian Community Health Survey and the drug claimsdatabase of the Ontario Drug Benefit Program. The analysis pertains to cardiovascular and diabetes drugs because they are commonly used, and almost all are prescribed on a regular basis.

    Release date: 2013-01-16
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Analysis (14)

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  • Articles and reports: 46-28-0001202200100001
    Description:

    When a survey publishes statistics with a quality indicator, it is usually derived from measures based on sampling theory. The production of quality indicators is a significant challenge when statistics are produced using alternative sources for which no sampling is done. This paper describes a new method used to create a quality indicator that combines indicators obtained at different stages of data processing. An example of the application of the method in the Canadian Housing Statistics Program is provided in the Appendix.

    Release date: 2022-01-06

  • Articles and reports: 11-522-X202100100015
    Description: National statistical agencies such as Statistics Canada have a responsibility to convey the quality of statistical information to users. The methods traditionally used to do this are based on measures of sampling error. As a result, they are not adapted to the estimates produced using administrative data, for which the main sources of error are not due to sampling. A more suitable approach to reporting the quality of estimates presented in a multidimensional table is described in this paper. Quality indicators were derived for various post-acquisition processing steps, such as linkage, geocoding and imputation, by estimation domain. A clustering algorithm was then used to combine domains with similar quality levels for a given estimate. Ratings to inform users of the relative quality of estimates across domains were assigned to the groups created. This indicator, called the composite quality indicator (CQI), was developed and experimented with in the Canadian Housing Statistics Program (CHSP), which aims to produce official statistics on the residential housing sector in Canada using multiple administrative data sources.

    Keywords: Unsupervised machine learning, quality assurance, administrative data, data integration, clustering.

    Release date: 2021-10-22

  • Articles and reports: 11F0019M2019025
    Description:

    This study identifies gig workers based on characteristics of their work arrangements and how these are reported in tax data. It introduces a definition of gig work specific to the way work arrangements are reported in the Canadian tax system and estimates the size of the gig economy in Canada using administrative data. The share of gig workers among all workers rose from 5.5% in 2005 to 8.2% in 2016. Some of this increase coincided with the introduction and proliferation of online platforms. The analysis highlights gender differences in the trends and characteristics of gig workers. By linking administrative data to 2016 Census microdata, this study also examines educational and occupational differences in the prevalence of gig workers.

    Release date: 2019-12-16

  • Articles and reports: 75F0002M2019007
    Description:

    Not having a Social Insurance Number (SIN) and not filing taxes may represent challenges to access government programs and supports such as the Canada Education Savings Grant (CESG) and the Canada Learning Bond (CLB). Limited data availability has prevented a full assessment of the extent of these access challenges. This study attempts to address this knowledge gap by analyzing overall differences in SIN possession and tax-filing uptake by family income, levels of parental education, family type and Indigenous identity of the child and age of children using the 2016 Census data augmented with tax-filing and Social Insurance Number possession indicator flags.

    Release date: 2019-06-21

  • Articles and reports: 11-633-X2018013
    Description:

    Since 2008, a number of population censuses have been linked to administrative health data and to financial data. These linked datasets have been instrumental in examining health inequalities and have been used in environmental health research. This paper describes the creation of the 1996 Canadian Census Health and Environment Cohort (CanCHEC)—3.57 million respondents to the census long-form questionnaire who were retrospectively followed for mortality and mobility for 16.6 years from 1996 to 2012. The 1996 CanCHEC was limited to census respondents who were aged 19 or older on Census Day (May 14, 1996), were residents of Canada, were not residents of institutions, and had filed an income tax return. These respondents were linked to death records from the Canadian Mortality Database or to the T1 Personal Master File, and to a postal code history from a variety of sources. This is the third in a set of CanCHECs that, when combined, make it possible to examine mortality trends and environmental exposures by socioeconomic characteristics over three census cycles and 21 years of census, tax, and mortality data. This report describes linkage methodologies, validation and bias assessment, and the characteristics of the 1996 CanCHEC. Representativeness of the 1996 CanCHEC relative to the adult population of Canada is also assessed.

    Release date: 2018-01-22

  • Articles and reports: 11-522-X201700014715
    Description:

    In preparation for 2021 UK Census the ONS has committed to an extensive research programme exploring how linked administrative data can be used to support conventional statistical processes. Item-level edit and imputation (E&I) will play an important role in adjusting the 2021 Census database. However, uncertainty associated with the accuracy and quality of available administrative data renders the efficacy of an integrated census-administrative data approach to E&I unclear. Current constraints that dictate an anonymised ‘hash-key’ approach to record linkage to ensure confidentiality add to that uncertainty. Here, we provide preliminary results from a simulation study comparing the predictive and distributional accuracy of the conventional E&I strategy implemented in CANCEIS for the 2011 UK Census to that of an integrated approach using synthetic administrative data with systematically increasing error as auxiliary information. In this initial phase of research we focus on imputing single year of age. The aim of the study is to gain insight into whether auxiliary information from admin data can improve imputation estimates and where the different strategies fall on a continuum of accuracy.

    Release date: 2016-03-24

  • Articles and reports: 82-003-X201500214140
    Description:

    This study examines the feasibility and limitations of applying a non-categorical approach (focused on service utilization rather than on specific diagnoses) to administrative data in order to identify children with health problems.

    Release date: 2015-02-18

  • Articles and reports: 11-522-X201300014284
    Description:

    The decline in response rates observed by several national statistical institutes, their desire to limit response burden and the significant budget pressures they face support greater use of administrative data to produce statistical information. The administrative data sources they must consider have to be evaluated according to several aspects to determine their fitness for use. Statistics Canada recently developed a process to evaluate administrative data sources for use as inputs to the statistical information production process. This evaluation is conducted in two phases. The initial phase requires access only to the metadata associated with the administrative data considered, whereas the second phase uses a version of data that can be evaluated. This article outlines the evaluation process and tool.

    Release date: 2014-10-31

  • Articles and reports: 82-003-X201300111764
    Geography: Province or territory
    Description:

    This study compares two sources of information about prescription drug use by people aged 65 or older in Ontario - the Canadian Community Health Survey and the drug claimsdatabase of the Ontario Drug Benefit Program. The analysis pertains to cardiovascular and diabetes drugs because they are commonly used, and almost all are prescribed on a regular basis.

    Release date: 2013-01-16

  • Articles and reports: 11-522-X20050019458
    Description:

    The proposed paper presents an alternative methodology that gives the data the possibility of defining homogenous groups determined by a bottom up classification of the values of observed details. The problem is then to assign a non respondent business to one of these groups. Several assignment procedures, based on explanatory variables available in the tax returns, are compared, using gross or distributed data: parametric and non parametric classification analyses, log linear models, etc.

    Release date: 2007-03-02
Reference (1)

Reference (1) ((1 result))

  • Surveys and statistical programs – Documentation: 75-005-M2015001
    Description:

    Using the experimental Workplace Survey conducted in 2011, this technical document summarizes the main results and evaluates the quality of the data.

    Release date: 2015-04-28
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