Frames and coverage

Filter results by

Search Help
Currently selected filters that can be removed

Keyword(s)

Geography

1 facets displayed. 0 facets selected.

Survey or statistical program

3 facets displayed. 0 facets selected.

Content

1 facets displayed. 0 facets selected.
Sort Help
entries

Results

All (70)

All (70) (0 to 10 of 70 results)

  • Articles and reports: 75F0002M2023001
    Description: This discussion paper describes the work being achieved and undertaken by Statistics Canada, in partnership with the Treasury Board of Canada Secretariat, the Department of Finance Canada and the Privy Council Office, on developing the Quality of Life Framework for Canada and related outputs, including an online Hub. This is the first paper in a series that will provide updates on the progress of work relating to the Framework.
    Release date: 2023-04-19

  • Articles and reports: 36-28-0001202300100003
    Description: Quality of life and well-being research often involves survey content that is subjective in nature, for example questions pertaining to life satisfaction. Two phenomena impacting responses to self-reported life satisfaction are studied across a range of social surveys: the framing effect, where a respondent’s answer is influenced by the theme of the survey or its content; and the mode effect, where a respondent’s answer is influenced by the method in which survey data is collected (with an interviewer, through an online collection portal, etc.). The objective of this paper is to document the effect that survey collection and survey content have on Canadians’ self-reported satisfaction with their lives. The impact of these effects on life satisfaction responses is measured across three Statistics Canada survey series: the General Social Survey, the Canadian Community Health Survey, and the Canadian Social Survey.
    Release date: 2023-01-25

  • Articles and reports: 12-001-X201900300008
    Description:

    Dual frame surveys are useful when no single frame with adequate coverage exists. However estimators from dual frame designs require knowledge of the frame memberships of each sampled unit. When this information is not available from the frame itself, it is often collected from the respondent. When respondents provide incorrect membership information, the resulting estimators of means or totals can be biased. A method for reducing this bias, using accurate membership information obtained about a subsample of respondents, is proposed. The properties of the new estimator are examined and compared to alternative estimators. The proposed estimator is applied to the data from the motivating example, which was a recreational angler survey, using an address frame and an incomplete fishing license frame.

    Release date: 2019-12-17

  • Stats in brief: 11-629-X2019004
    Description:

    This video explains the Necessity and Proportionality Framework, which assesses data sensitivity and gathering in a more integrated way while ensuring the data needs of Canadians are met.

    Release date: 2019-11-26

  • Surveys and statistical programs – Documentation: 98-303-X
    Description:

    The Coverage Technical Report will present the error included in census data that results from either persons being missed (not enumerated) or from persons being enumerated more than once by the 2016 Census. The population coverage error is one of the most important types of errors because it affects not only the accuracy of population counts, but also the accuracy of all the census data results describing the characteristics of the population universe.

    Release date: 2019-11-13

  • Stats in brief: 11-629-X2016003
    Description:

    Discover how the Enterprise Portfolio Management team (EPM) supports some of Canada’s largest enterprises.

    Release date: 2016-06-02

  • Surveys and statistical programs – Documentation: 11-522-X201700014708
    Description:

    Statistics Canada’s Household Survey Frames (HSF) Programme provides various universe files that can be used alone or in combination to improve survey design, sampling, collection, and processing in the traditional “need to contact a household model.” Even as surveys are migrating onto these core suite of products, the HSF is starting to plan the changes to infrastructure, organisation, and linkages with other data assets in Statistics Canada that will help enable a shift to increased use of a wide variety of administrative data as input to the social statistics programme. The presentation will provide an overview of the HSF Programme, foundational concepts that will need to be implemented to expand linkage potential, and will identify strategic research being under-taken toward 2021.

    Release date: 2016-03-24

  • Articles and reports: 12-001-X201500114149
    Description:

    This paper introduces a general framework for deriving the optimal inclusion probabilities for a variety of survey contexts in which disseminating survey estimates of pre-established accuracy for a multiplicity of both variables and domains of interest is required. The framework can define either standard stratified or incomplete stratified sampling designs. The optimal inclusion probabilities are obtained by minimizing costs through an algorithm that guarantees the bounding of sampling errors at the domains level, assuming that the domain membership variables are available in the sampling frame. The target variables are unknown, but can be predicted with suitable super-population models. The algorithm takes properly into account this model uncertainty. Some experiments based on real data show the empirical properties of the algorithm.

    Release date: 2015-06-29

  • Articles and reports: 12-001-X201400214128
    Description:

    Users, funders and providers of official statistics want estimates that are “wider, deeper, quicker, better, cheaper” (channeling Tim Holt, former head of the UK Office for National Statistics), to which I would add “more relevant” and “less burdensome”. Since World War II, we have relied heavily on the probability sample survey as the best we could do - and that best being very good - to meet these goals for estimates of household income and unemployment, self-reported health status, time use, crime victimization, business activity, commodity flows, consumer and business expenditures, et al. Faced with secularly declining unit and item response rates and evidence of reporting error, we have responded in many ways, including the use of multiple survey modes, more sophisticated weighting and imputation methods, adaptive design, cognitive testing of survey items, and other means to maintain data quality. For statistics on the business sector, in order to reduce burden and costs, we long ago moved away from relying solely on surveys to produce needed estimates, but, to date, we have not done that for household surveys, at least not in the United States. I argue that we can and must move from a paradigm of producing the best estimates possible from a survey to that of producing the best possible estimates to meet user needs from multiple data sources. Such sources include administrative records and, increasingly, transaction and Internet-based data. I provide two examples - household income and plumbing facilities - to illustrate my thesis. I suggest ways to inculcate a culture of official statistics that focuses on the end result of relevant, timely, accurate and cost-effective statistics and treats surveys, along with other data sources, as means to that end.

    Release date: 2014-12-19

  • Surveys and statistical programs – Documentation: 11-522-X201300014269
    Description:

    The Census Overcoverage Study (COS) is a critical post-census coverage measurement study. Its main objective is to produce estimates of the number of people erroneously enumerated, by province and territory, study the characteristics of individuals counted multiple times and identify possible reasons for the errors. The COS is based on the sampling and clerical review of groups of connected records that are built by linking the census response database to an administrative frame, and to itself. In this paper we describe the new 2011 COS methodology. This methodology has incorporated numerous improvements including a greater use of probabilistic record-linkage, the estimation of linking parameters with an Expectation-Maximization (E-M) algorithm, and the efficient use of household information to detect more overcoverage cases.

    Release date: 2014-10-31
Data (0)

Data (0) (0 results)

No content available at this time.

Analysis (60)

Analysis (60) (0 to 10 of 60 results)

  • Articles and reports: 75F0002M2023001
    Description: This discussion paper describes the work being achieved and undertaken by Statistics Canada, in partnership with the Treasury Board of Canada Secretariat, the Department of Finance Canada and the Privy Council Office, on developing the Quality of Life Framework for Canada and related outputs, including an online Hub. This is the first paper in a series that will provide updates on the progress of work relating to the Framework.
    Release date: 2023-04-19

  • Articles and reports: 36-28-0001202300100003
    Description: Quality of life and well-being research often involves survey content that is subjective in nature, for example questions pertaining to life satisfaction. Two phenomena impacting responses to self-reported life satisfaction are studied across a range of social surveys: the framing effect, where a respondent’s answer is influenced by the theme of the survey or its content; and the mode effect, where a respondent’s answer is influenced by the method in which survey data is collected (with an interviewer, through an online collection portal, etc.). The objective of this paper is to document the effect that survey collection and survey content have on Canadians’ self-reported satisfaction with their lives. The impact of these effects on life satisfaction responses is measured across three Statistics Canada survey series: the General Social Survey, the Canadian Community Health Survey, and the Canadian Social Survey.
    Release date: 2023-01-25

  • Articles and reports: 12-001-X201900300008
    Description:

    Dual frame surveys are useful when no single frame with adequate coverage exists. However estimators from dual frame designs require knowledge of the frame memberships of each sampled unit. When this information is not available from the frame itself, it is often collected from the respondent. When respondents provide incorrect membership information, the resulting estimators of means or totals can be biased. A method for reducing this bias, using accurate membership information obtained about a subsample of respondents, is proposed. The properties of the new estimator are examined and compared to alternative estimators. The proposed estimator is applied to the data from the motivating example, which was a recreational angler survey, using an address frame and an incomplete fishing license frame.

    Release date: 2019-12-17

  • Stats in brief: 11-629-X2019004
    Description:

    This video explains the Necessity and Proportionality Framework, which assesses data sensitivity and gathering in a more integrated way while ensuring the data needs of Canadians are met.

    Release date: 2019-11-26

  • Stats in brief: 11-629-X2016003
    Description:

    Discover how the Enterprise Portfolio Management team (EPM) supports some of Canada’s largest enterprises.

    Release date: 2016-06-02

  • Articles and reports: 12-001-X201500114149
    Description:

    This paper introduces a general framework for deriving the optimal inclusion probabilities for a variety of survey contexts in which disseminating survey estimates of pre-established accuracy for a multiplicity of both variables and domains of interest is required. The framework can define either standard stratified or incomplete stratified sampling designs. The optimal inclusion probabilities are obtained by minimizing costs through an algorithm that guarantees the bounding of sampling errors at the domains level, assuming that the domain membership variables are available in the sampling frame. The target variables are unknown, but can be predicted with suitable super-population models. The algorithm takes properly into account this model uncertainty. Some experiments based on real data show the empirical properties of the algorithm.

    Release date: 2015-06-29

  • Articles and reports: 12-001-X201400214128
    Description:

    Users, funders and providers of official statistics want estimates that are “wider, deeper, quicker, better, cheaper” (channeling Tim Holt, former head of the UK Office for National Statistics), to which I would add “more relevant” and “less burdensome”. Since World War II, we have relied heavily on the probability sample survey as the best we could do - and that best being very good - to meet these goals for estimates of household income and unemployment, self-reported health status, time use, crime victimization, business activity, commodity flows, consumer and business expenditures, et al. Faced with secularly declining unit and item response rates and evidence of reporting error, we have responded in many ways, including the use of multiple survey modes, more sophisticated weighting and imputation methods, adaptive design, cognitive testing of survey items, and other means to maintain data quality. For statistics on the business sector, in order to reduce burden and costs, we long ago moved away from relying solely on surveys to produce needed estimates, but, to date, we have not done that for household surveys, at least not in the United States. I argue that we can and must move from a paradigm of producing the best estimates possible from a survey to that of producing the best possible estimates to meet user needs from multiple data sources. Such sources include administrative records and, increasingly, transaction and Internet-based data. I provide two examples - household income and plumbing facilities - to illustrate my thesis. I suggest ways to inculcate a culture of official statistics that focuses on the end result of relevant, timely, accurate and cost-effective statistics and treats surveys, along with other data sources, as means to that end.

    Release date: 2014-12-19

  • Articles and reports: 12-001-X201100211608
    Description:

    Designs and estimators for the single frame surveys currently used by U.S. government agencies were developed in response to practical problems. Federal household surveys now face challenges of decreasing response rates and frame coverage, higher data collection costs, and increasing demand for small area statistics. Multiple frame surveys, in which independent samples are drawn from separate frames, can be used to help meet some of these challenges. Examples include combining a list frame with an area frame or using two frames to sample landline telephone households and cellular telephone households. We review point estimators and weight adjustments that can be used to analyze multiple frame surveys with standard survey software, and summarize construction of replicate weights for variance estimation. Because of their increased complexity, multiple frame surveys face some challenges not found in single frame surveys. We investigate misclassification bias in multiple frame surveys, and propose a method for correcting for this bias when misclassification probabilities are known. Finally, we discuss research that is needed on nonsampling errors with multiple frame surveys.

    Release date: 2011-12-21

  • Articles and reports: 12-001-X201100111443
    Description:

    Dual frame telephone surveys are becoming common in the U.S. because of the incompleteness of the landline frame as people transition to cell phones. This article examines nonsampling errors in dual frame telephone surveys. Even though nonsampling errors are ignored in much of the dual frame literature, we find that under some conditions substantial biases may arise in dual frame telephone surveys due to these errors. We specifically explore biases due to nonresponse and measurement error in these telephone surveys. To reduce the bias resulting from these errors, we propose dual frame sampling and weighting methods. The compositing factor for combining the estimates from the two frames is shown to play an important role in reducing nonresponse bias.

    Release date: 2011-06-29

  • Articles and reports: 11-522-X200800010972
    Description:

    Background: Evaluation of the coverage that results from linking routinely collected administrative hospital data with survey data is an important preliminary step to undertaking analyses based on the linked file. Data and methods: To evaluate the coverage of the linkage between data from cycle 1.1 of the Canadian Community Health Survey (CCHS) and in-patient hospital data (Health Person-Oriented Information or HPOI), the number of people admitted to hospital according to HPOI was compared with the weighted estimate for CCHS respondents who were successfully linked to HPOI. Differences between HPOI and the linked and weighted CCHS estimate indicated linkage failure and/or undercoverage. Results: According to HPOI, from September 2000 through November 2001, 1,572,343 people (outside Quebec) aged 12 or older were hospitalized. Weighted estimates from the linked CCHS, adjusted for agreement to link and plausible health number, were 7.7% lower. Coverage rates were similar for males and females. Provincial rates did not differ from those for the rest of Canada, although differences were apparent for the territories. Coverage rates were significantly lower among people aged 75 or older than among those aged 12 to 74.

    Release date: 2009-12-03
Reference (10)

Reference (10) ((10 results))

  • Surveys and statistical programs – Documentation: 98-303-X
    Description:

    The Coverage Technical Report will present the error included in census data that results from either persons being missed (not enumerated) or from persons being enumerated more than once by the 2016 Census. The population coverage error is one of the most important types of errors because it affects not only the accuracy of population counts, but also the accuracy of all the census data results describing the characteristics of the population universe.

    Release date: 2019-11-13

  • Surveys and statistical programs – Documentation: 11-522-X201700014708
    Description:

    Statistics Canada’s Household Survey Frames (HSF) Programme provides various universe files that can be used alone or in combination to improve survey design, sampling, collection, and processing in the traditional “need to contact a household model.” Even as surveys are migrating onto these core suite of products, the HSF is starting to plan the changes to infrastructure, organisation, and linkages with other data assets in Statistics Canada that will help enable a shift to increased use of a wide variety of administrative data as input to the social statistics programme. The presentation will provide an overview of the HSF Programme, foundational concepts that will need to be implemented to expand linkage potential, and will identify strategic research being under-taken toward 2021.

    Release date: 2016-03-24

  • Surveys and statistical programs – Documentation: 11-522-X201300014269
    Description:

    The Census Overcoverage Study (COS) is a critical post-census coverage measurement study. Its main objective is to produce estimates of the number of people erroneously enumerated, by province and territory, study the characteristics of individuals counted multiple times and identify possible reasons for the errors. The COS is based on the sampling and clerical review of groups of connected records that are built by linking the census response database to an administrative frame, and to itself. In this paper we describe the new 2011 COS methodology. This methodology has incorporated numerous improvements including a greater use of probabilistic record-linkage, the estimation of linking parameters with an Expectation-Maximization (E-M) algorithm, and the efficient use of household information to detect more overcoverage cases.

    Release date: 2014-10-31

  • Surveys and statistical programs – Documentation: 87-542-X2011001
    Geography: Canada
    Description:

    The first issue of the series presents the Conceptual Framework for Culture Statistics 2011, a revision of the 2004 Canadian Framework for Culture Statistics.

    The conceptual framework contains an official statistical definition of culture and describes a set of culture domains that can be used to measure culture from creation to use.

    Release date: 2011-10-24

  • Surveys and statistical programs – Documentation: 87-542-X2011002
    Geography: Canada
    Description:

    The second issue of this series is a companion piece to the Conceptual Framework for Culture Statistics 2011, a revision to the 2004 Canadian Framework for Culture Statistics.

    The guide maps the 2011 Canadian framework for culture statistics to the following Statistics Canada's standard classification systems: the North American Industry Classification System (NAICS) 2007, the North American Product Classification System (NAPCS) - Canada (Provisional Version 0.1), National Occupational Classification - Statistics (NOC-S) 2006 and Classification of Instructional Programs (CIP), Canada, 2000.

    It contains explanations, definitions and examples of how the classification codes are mapped to the conceptual framework. It also contains a series of tables that contain codes, by classification system, which help illustrate the framework domains and sub-domains, and flags those codes that do not map well to the framework.

    Release date: 2011-10-24

  • Surveys and statistical programs – Documentation: 87-542-X
    Geography: Canada
    Description:

    This series the Canadian Framework for Culture Statistics 2011 replaces the 2004 Canadian Framework for Culture Statistics (Catalogue 81-595-MIE2004021).

    The first issue of this series presents the conceptual framework, including a definition of culture, domains and sub-domains, and criteria for their inclusion in culture. The second issue is a guide that maps the conceptual framework to selected standard classification systems. It is intended to foster a standard approach to the measurement of culture in Canada.

    Release date: 2011-10-24

  • Surveys and statistical programs – Documentation: 92-567-X
    Description:

    The Coverage Technical Report will present the error included in census data that results from persons missed by the 2006 Census or persons enumerated in error. Population coverage errors are one of the most important types of error because they affect not only the accuracy of population counts but also the accuracy of all of the census data describing characteristics of the population universe.

    Release date: 2010-03-25

  • Surveys and statistical programs – Documentation: 92-394-X
    Description:

    This report deals with coverage errors that occur when persons, households, dwellings or families are missed or enumerated in error by the census. After the 2001 Census was taken, a number of studies were carried out to estimate gross undercoverage, gross overcoverage and net undercoverage. This report presents the results of the Dwelling Classification Study, the Reverse Record Check Study, the Automated Match Study and the Collective Dwelling Study. The report first describes census universes, coverage error and census collection and processing procedures that may result in coverage error. Then it gives estimates of net undercoverage for a number of demographic characteristics. After, the technical report presents the methodology and results of each coverage study and the estimates of coverage error after describing how the results of the various studies are combined. A historical perspective completes the product.

    Release date: 2004-11-25

  • Surveys and statistical programs – Documentation: 92-370-X
    Description:

    Series description

    This series includes five general reference products - the Preview of Products and Services; the Catalogue; the Dictionary; the Handbook and the Technical Reports - as well as geography reference products - GeoSuite and Reference Maps.

    Product description

    Technical Reports examine the quality of data from the 1996 Census, a large and complex undertaking. While considerable effort was taken to ensure high quality standards throughout each step, the results are subject to a certain degree of error. Each report looks at the collection and processing operations and presents results from data evaluation, as well as notes on historical comparability.

    Technical Reports are aimed at moderate and sophisticated users but are written in a manner which could make them useful to all census data users. Most of the technical reports have been cancelled, with the exception of Age, Sex, Marital Status and Common-law Status, Coverage and Sampling and Weighting. These reports will be available as bilingual publications as well as being available in both official languages on the Internet as free products.

    This report deals with coverage errors, which occured when persons, households, dwellings or families were missed by the 1996 Census or enumerated in error. Coverage errors are one of the most important types of error since they affect not only the accuracy of the counts of the various census universes but also the accuracy of all of the census data describing the characteristics of these universes. With this information, users can determine the risks involved in basing conclusions or decisions on census data.

    Release date: 1999-12-14

  • Surveys and statistical programs – Documentation: 5241
    Description: The SRGD is conducting a Global Positioning System (GPS) and digital mapping test to improve Statistic Canada's rural dwelling inventory by collecting dwelling identifiers to be used by field collection staff. In rural areas dwelling identification can be difficult where there is an absence of civic style addresses. The test is evaluating alternative methods for dwelling identification including the collection of GPS coordinates and digital photos using a mapping application and a digital tablet
Date modified: