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- Articles and reports: 12-001-X202200100006Description:
In the last two decades, survey response rates have been steadily falling. In that context, it has become increasingly important for statistical agencies to develop and use methods that reduce the adverse effects of non-response on the accuracy of survey estimates. Follow-up of non-respondents may be an effective, albeit time and resource-intensive, remedy for non-response bias. We conducted a simulation study using real business survey data to shed some light on several questions about non-response follow-up. For instance, assuming a fixed non-response follow-up budget, what is the best way to select non-responding units to be followed up? How much effort should be dedicated to repeatedly following up non-respondents until a response is received? Should they all be followed up or a sample of them? If a sample is followed up, how should it be selected? We compared Monte Carlo relative biases and relative root mean square errors under different follow-up sampling designs, sample sizes and non-response scenarios. We also determined an expression for the minimum follow-up sample size required to expend the budget, on average, and showed that it maximizes the expected response rate. A main conclusion of our simulation experiment is that this sample size also appears to approximately minimize the bias and mean square error of the estimates.
Release date: 2022-06-21 - Articles and reports: 11-522-X202100100006Description:
In the context of its "admin-first" paradigm, Statistics Canada is prioritizing the use of non-survey sources to produce official statistics. This paradigm critically relies on non-survey sources that may have a nearly perfect coverage of some target populations, including administrative files or big data sources. Yet, this coverage must be measured, e.g., by applying the capture-recapture method, where they are compared to other sources with good coverage of the same populations, including a census. However, this is a challenging exercise in the presence of linkage errors, which arise inevitably when the linkage is based on quasi-identifiers, as is typically the case. To address the issue, a new methodology is described where the capture-recapture method is enhanced with a new error model that is based on the number of links adjacent to a given record. It is applied in an experiment with public census data.
Key Words: dual system estimation, data matching, record linkage, quality, data integration, big data.
Release date: 2021-10-22 - 3. Canadian Cancer Treatment Linkage Project ArchivedArticles and reports: 11-633-X2018016Description:
Record linkage has been identified as a potential mechanism to add treatment information to the Canadian Cancer Registry (CCR). The purpose of the Canadian Cancer Treatment Linkage Project (CCTLP) pilot is to add surgical treatment data to the CCR. The Discharge Abstract Database (DAD) and the National Ambulatory Care Reporting System (NACRS) were linked to the CCR, and surgical treatment data were extracted. The project was funded through the Cancer Data Development Initiative (CDDI) of the Canadian Partnership Against Cancer (CPAC).
The CCTLP was developed as a feasibility study in which patient records from the CCR would be linked to surgical treatment records in the DAD and NACRS databases, maintained by the Canadian Institute for Health Information. The target cohort to whom surgical treatment data would be linked was patients aged 19 or older registered on the CCR (2010 through 2012). The linkage was completed in Statistics Canada’s Social Data Linkage Environment (SDLE).
Release date: 2018-03-27 - Articles and reports: 12-001-X201600114543Description:
The regression estimator is extensively used in practice because it can improve the reliability of the estimated parameters of interest such as means or totals. It uses control totals of variables known at the population level that are included in the regression set up. In this paper, we investigate the properties of the regression estimator that uses control totals estimated from the sample, as well as those known at the population level. This estimator is compared to the regression estimators that strictly use the known totals both theoretically and via a simulation study.
Release date: 2016-06-22 - Articles and reports: 11-522-X201700014711Description:
After the 2010 Census, the U.S. Census Bureau conducted two separate research projects matching survey data to databases. One study matched to the third-party database Accurint, and the other matched to U.S. Postal Service National Change of Address (NCOA) files. In both projects, we evaluated response error in reported move dates by comparing the self-reported move date to records in the database. We encountered similar challenges in the two projects. This paper discusses our experience using “big data” as a comparison source for survey data and our lessons learned for future projects similar to the ones we conducted.
Release date: 2016-03-24 - 6. Student Pathways and Graduate Outcomes ArchivedSurveys and statistical programs – Documentation: 11-522-X201700014717Description:
Files with linked data from the Statistics Canada, Postsecondary Student Information System (PSIS) and tax data can be used to examine the trajectories of students who pursue postsecondary education (PSE) programs and their post-schooling labour market outcomes. On one hand, administrative data on students linked longitudinally can provide aggregate information on student pathways during postsecondary studies such as persistence rates, graduation rates, mobility, etc. On the other hand, the tax data could supplement the PSIS data to provide information on employment outcomes such as average and median earnings or earnings progress by employment sector (industry), field of study, education level and/or other demographic information, year over year after graduation. Two longitudinal pilot studies have been done using administrative data on postsecondary students of Maritimes institutions which have been longitudinally linked and linked to Statistics Canada Ttx data (the T1 Family File) for relevant years. This article first focuses on the quality of information in the administrative data and the methodology used to conduct these longitudinal studies and derive indicators. Second, it will focus on some limitations when using administrative data, rather than a survey, to define some concepts.
Release date: 2016-03-24 - Articles and reports: 11-522-X201300014264Description:
While wetlands represent only 6.4% of the world’s surface area, they are essential to the survival of terrestrial species. These ecosystems require special attention in Canada, since that is where nearly 25% of the world’s wetlands are found. Environment Canada (EC) has massive databases that contain all kinds of wetland information from various sources. Before the information in these databases could be used for any environmental initiative, it had to be classified and its quality had to be assessed. In this paper, we will give an overview of the joint pilot project carried out by EC and Statistics Canada to assess the quality of the information contained in these databases, which has characteristics specific to big data, administrative data and survey data.
Release date: 2014-10-31 - Articles and reports: 11-522-X201300014284Description:
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 - 9. Deterministic and probabilistic record linkage ArchivedArticles and reports: 11-522-X200600110404Description:
Pursuing reduction in cost and response burden in survey programs has led to increased use of information available in administrative databases. Linkages between these two data sources is a way to exploit their complementary nature and maximize their respective usefulness. This paper discusses the various ways we have performed record linkage between the Canadian Community Health Survey (CCHS) and the Health Person-Oriented Information (HPOI) databases. The files resulting from selected linkage methods are used in an analysis of risk factors for having been hospitalized for heart disease. The sensitivity of the analysis with respect to the various linkage approaches is investigated.
Release date: 2008-03-17
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- Articles and reports: 12-001-X202200100006Description:
In the last two decades, survey response rates have been steadily falling. In that context, it has become increasingly important for statistical agencies to develop and use methods that reduce the adverse effects of non-response on the accuracy of survey estimates. Follow-up of non-respondents may be an effective, albeit time and resource-intensive, remedy for non-response bias. We conducted a simulation study using real business survey data to shed some light on several questions about non-response follow-up. For instance, assuming a fixed non-response follow-up budget, what is the best way to select non-responding units to be followed up? How much effort should be dedicated to repeatedly following up non-respondents until a response is received? Should they all be followed up or a sample of them? If a sample is followed up, how should it be selected? We compared Monte Carlo relative biases and relative root mean square errors under different follow-up sampling designs, sample sizes and non-response scenarios. We also determined an expression for the minimum follow-up sample size required to expend the budget, on average, and showed that it maximizes the expected response rate. A main conclusion of our simulation experiment is that this sample size also appears to approximately minimize the bias and mean square error of the estimates.
Release date: 2022-06-21 - Articles and reports: 11-522-X202100100006Description:
In the context of its "admin-first" paradigm, Statistics Canada is prioritizing the use of non-survey sources to produce official statistics. This paradigm critically relies on non-survey sources that may have a nearly perfect coverage of some target populations, including administrative files or big data sources. Yet, this coverage must be measured, e.g., by applying the capture-recapture method, where they are compared to other sources with good coverage of the same populations, including a census. However, this is a challenging exercise in the presence of linkage errors, which arise inevitably when the linkage is based on quasi-identifiers, as is typically the case. To address the issue, a new methodology is described where the capture-recapture method is enhanced with a new error model that is based on the number of links adjacent to a given record. It is applied in an experiment with public census data.
Key Words: dual system estimation, data matching, record linkage, quality, data integration, big data.
Release date: 2021-10-22 - 3. Canadian Cancer Treatment Linkage Project ArchivedArticles and reports: 11-633-X2018016Description:
Record linkage has been identified as a potential mechanism to add treatment information to the Canadian Cancer Registry (CCR). The purpose of the Canadian Cancer Treatment Linkage Project (CCTLP) pilot is to add surgical treatment data to the CCR. The Discharge Abstract Database (DAD) and the National Ambulatory Care Reporting System (NACRS) were linked to the CCR, and surgical treatment data were extracted. The project was funded through the Cancer Data Development Initiative (CDDI) of the Canadian Partnership Against Cancer (CPAC).
The CCTLP was developed as a feasibility study in which patient records from the CCR would be linked to surgical treatment records in the DAD and NACRS databases, maintained by the Canadian Institute for Health Information. The target cohort to whom surgical treatment data would be linked was patients aged 19 or older registered on the CCR (2010 through 2012). The linkage was completed in Statistics Canada’s Social Data Linkage Environment (SDLE).
Release date: 2018-03-27 - Articles and reports: 12-001-X201600114543Description:
The regression estimator is extensively used in practice because it can improve the reliability of the estimated parameters of interest such as means or totals. It uses control totals of variables known at the population level that are included in the regression set up. In this paper, we investigate the properties of the regression estimator that uses control totals estimated from the sample, as well as those known at the population level. This estimator is compared to the regression estimators that strictly use the known totals both theoretically and via a simulation study.
Release date: 2016-06-22 - Articles and reports: 11-522-X201700014711Description:
After the 2010 Census, the U.S. Census Bureau conducted two separate research projects matching survey data to databases. One study matched to the third-party database Accurint, and the other matched to U.S. Postal Service National Change of Address (NCOA) files. In both projects, we evaluated response error in reported move dates by comparing the self-reported move date to records in the database. We encountered similar challenges in the two projects. This paper discusses our experience using “big data” as a comparison source for survey data and our lessons learned for future projects similar to the ones we conducted.
Release date: 2016-03-24 - Articles and reports: 11-522-X201300014264Description:
While wetlands represent only 6.4% of the world’s surface area, they are essential to the survival of terrestrial species. These ecosystems require special attention in Canada, since that is where nearly 25% of the world’s wetlands are found. Environment Canada (EC) has massive databases that contain all kinds of wetland information from various sources. Before the information in these databases could be used for any environmental initiative, it had to be classified and its quality had to be assessed. In this paper, we will give an overview of the joint pilot project carried out by EC and Statistics Canada to assess the quality of the information contained in these databases, which has characteristics specific to big data, administrative data and survey data.
Release date: 2014-10-31 - Articles and reports: 11-522-X201300014284Description:
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 - 8. Deterministic and probabilistic record linkage ArchivedArticles and reports: 11-522-X200600110404Description:
Pursuing reduction in cost and response burden in survey programs has led to increased use of information available in administrative databases. Linkages between these two data sources is a way to exploit their complementary nature and maximize their respective usefulness. This paper discusses the various ways we have performed record linkage between the Canadian Community Health Survey (CCHS) and the Health Person-Oriented Information (HPOI) databases. The files resulting from selected linkage methods are used in an analysis of risk factors for having been hospitalized for heart disease. The sensitivity of the analysis with respect to the various linkage approaches is investigated.
Release date: 2008-03-17
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- 1. Student Pathways and Graduate Outcomes ArchivedSurveys and statistical programs – Documentation: 11-522-X201700014717Description:
Files with linked data from the Statistics Canada, Postsecondary Student Information System (PSIS) and tax data can be used to examine the trajectories of students who pursue postsecondary education (PSE) programs and their post-schooling labour market outcomes. On one hand, administrative data on students linked longitudinally can provide aggregate information on student pathways during postsecondary studies such as persistence rates, graduation rates, mobility, etc. On the other hand, the tax data could supplement the PSIS data to provide information on employment outcomes such as average and median earnings or earnings progress by employment sector (industry), field of study, education level and/or other demographic information, year over year after graduation. Two longitudinal pilot studies have been done using administrative data on postsecondary students of Maritimes institutions which have been longitudinally linked and linked to Statistics Canada Ttx data (the T1 Family File) for relevant years. This article first focuses on the quality of information in the administrative data and the methodology used to conduct these longitudinal studies and derive indicators. Second, it will focus on some limitations when using administrative data, rather than a survey, to define some concepts.
Release date: 2016-03-24
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