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- Articles and reports: 11-522-X202200100003Description: Estimation at fine levels of aggregation is necessary to better describe society. Small area estimation model-based approaches that combine sparse survey data with rich data from auxiliary sources have been proven useful to improve the reliability of estimates for small domains. Considered here is a scenario where small area model-based estimates, produced at a given aggregation level, needed to be disaggregated to better describe the social structure at finer levels. For this scenario, an allocation method was developed to implement the disaggregation, overcoming challenges associated with data availability and model development at such fine levels. The method is applied to adult literacy and numeracy estimation at the county-by-group-level, using data from the U.S. Program for the International Assessment of Adult Competencies. In this application the groups are defined in terms of age or education, but the method could be applied to estimation of other equity-deserving groups.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100005Description: Sampling variance smoothing is an important topic in small area estimation. In this paper, we propose sampling variance smoothing methods for small area proportion estimation. In particular, we consider the generalized variance function and design effect methods for sampling variance smoothing. We evaluate and compare the smoothed sampling variances and small area estimates based on the smoothed variance estimates through analysis of survey data from Statistics Canada. The results from real data analysis indicate that the proposed sampling variance smoothing methods work very well for small area estimation.Release date: 2024-03-25
- 3. Measuring the number of food aid recipients ArchivedArticles and reports: 11-522-X202200100013Description: Respondents to typical household surveys tend to significantly underreport their potential use of food aid distributed by associations. This underreporting is most likely related to the social stigma felt by people experiencing great financial difficulty. As a result, survey estimates of the number of recipients of that aid are much lower than the direct counts from the associations. Those counts tend to overestimate due to double counting. Through its adapted protocol, the Enquête Aide alimentaire (EAA) collected in late 2021 in France at a sample of sites of food aid distribution associations, controls the biases that affect the other sources and determines to what extent this aid is used.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100014Description: Ethnic minorities are often underrepresented in survey research, due to the challenges many researchers face in including these populations. While some studies discuss several methods in comparison, few have directly compared these methods empirically, leaving researchers seeking to include ethnic minorities in their studies unsure of their best options. In this article, I briefly review the methodological and ethical reasons for increasing ethnic minority representation in social science research, as well as challenges of doing so. I then present findings from ten studies which empirically compare methods of sampling and/or recruiting ethnic minority individuals. Finally, I discuss some implications for future research.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100015Description: We present design-based Horvitz-Thompson and multiplicity estimators of the population size, as well as of the total and mean of a response variable associated with the elements of a hidden population to be used with the link-tracing sampling variant proposed by Félix-Medina and Thompson (2004). Since the computation of the estimators requires to know the inclusion probabilities of the sampled people, but they are unknown, we propose a Bayesian model which allows us to estimate them, and consequently to compute the estimators of the population parameters. The results of a small numeric study indicate that the performance of the proposed estimators is acceptable.Release date: 2024-03-25
- 6. From theory to practice: Lessons learned from implementing the Network Sampling with Memory method ArchivedArticles and reports: 11-522-X202200100016Description: To overcome the traditional drawbacks of chain sampling methods, the sampling method called “network sampling with memory” was developed. Its unique feature is to recreate, gradually in the field, a frame for the target population composed of individuals identified by respondents and to randomly draw future respondents from this frame, thereby minimizing selection bias. Tested for the first time in France between September 2020 and June 2021, for a survey among Chinese immigrants in Île-de-France (ChIPRe), this presentation describes the difficulties encountered during collection—sometimes contextual, due to the pandemic, but mostly inherent to the method.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100018Description: The Longitudinal Social Data Development Program (LSDDP) is a social data integration approach aimed at providing longitudinal analytical opportunities without imposing additional burden on respondents. The LSDDP uses a multitude of signals from different data sources for the same individual, which helps to better understand their interactions and track changes over time. This article looks at how the ethnicity status of people in Canada can be estimated at the most detailed disaggregated level possible using the results from a variety of business rules applied to linked data and to the LSDDP denominator. It will then show how improvements were obtained using machine learning methods, such as decision trees and random forest techniques.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100019Description: The purpose of this article is to compare the linkage results for individuals from French tax sources with those of the 2019 Enquête Annuelle de Recensement (EAR), obtained through different methods. Such a comparison will decide whether the Répertoires Statistiques d'Individus et de Logements (Résil) program should be equipped with a probabilistic matching tool for its administrative source identification and matching engine.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100020Description: The reconciliation of 2021 census dwellings with the new Statistical Building Register (SBgR) presented linkage challenges. The Census of Population collected information from various dwelling types. For a large proportion of the population, mailing addresses were at the centre: they were used for reaching out to people and collected as contact info. In parallel, the register environment has been evolving. The agency is transitioning from the Address Register (AR) to the SBgR holding both mailing and location addresses, while also covering non-residential buildings. The reconciliation was conducted using a combination of systems, notably the new Register Matching Engine (RME) for difficult cases. The RME holds an interesting range of sophisticated string comparators. A deterministic linkage approach was used, while incorporating some data knowledge like the entropy. Through metadata, the matching expert could also reduce the amounts of false positives and false negatives.Release date: 2024-03-25
- Articles and reports: 11-633-X2024001Description: The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 35 years.Release date: 2024-01-22
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Analysis (126)
Analysis (126) (0 to 10 of 126 results)
- Articles and reports: 11-522-X202200100003Description: Estimation at fine levels of aggregation is necessary to better describe society. Small area estimation model-based approaches that combine sparse survey data with rich data from auxiliary sources have been proven useful to improve the reliability of estimates for small domains. Considered here is a scenario where small area model-based estimates, produced at a given aggregation level, needed to be disaggregated to better describe the social structure at finer levels. For this scenario, an allocation method was developed to implement the disaggregation, overcoming challenges associated with data availability and model development at such fine levels. The method is applied to adult literacy and numeracy estimation at the county-by-group-level, using data from the U.S. Program for the International Assessment of Adult Competencies. In this application the groups are defined in terms of age or education, but the method could be applied to estimation of other equity-deserving groups.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100005Description: Sampling variance smoothing is an important topic in small area estimation. In this paper, we propose sampling variance smoothing methods for small area proportion estimation. In particular, we consider the generalized variance function and design effect methods for sampling variance smoothing. We evaluate and compare the smoothed sampling variances and small area estimates based on the smoothed variance estimates through analysis of survey data from Statistics Canada. The results from real data analysis indicate that the proposed sampling variance smoothing methods work very well for small area estimation.Release date: 2024-03-25
- 3. Measuring the number of food aid recipients ArchivedArticles and reports: 11-522-X202200100013Description: Respondents to typical household surveys tend to significantly underreport their potential use of food aid distributed by associations. This underreporting is most likely related to the social stigma felt by people experiencing great financial difficulty. As a result, survey estimates of the number of recipients of that aid are much lower than the direct counts from the associations. Those counts tend to overestimate due to double counting. Through its adapted protocol, the Enquête Aide alimentaire (EAA) collected in late 2021 in France at a sample of sites of food aid distribution associations, controls the biases that affect the other sources and determines to what extent this aid is used.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100014Description: Ethnic minorities are often underrepresented in survey research, due to the challenges many researchers face in including these populations. While some studies discuss several methods in comparison, few have directly compared these methods empirically, leaving researchers seeking to include ethnic minorities in their studies unsure of their best options. In this article, I briefly review the methodological and ethical reasons for increasing ethnic minority representation in social science research, as well as challenges of doing so. I then present findings from ten studies which empirically compare methods of sampling and/or recruiting ethnic minority individuals. Finally, I discuss some implications for future research.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100015Description: We present design-based Horvitz-Thompson and multiplicity estimators of the population size, as well as of the total and mean of a response variable associated with the elements of a hidden population to be used with the link-tracing sampling variant proposed by Félix-Medina and Thompson (2004). Since the computation of the estimators requires to know the inclusion probabilities of the sampled people, but they are unknown, we propose a Bayesian model which allows us to estimate them, and consequently to compute the estimators of the population parameters. The results of a small numeric study indicate that the performance of the proposed estimators is acceptable.Release date: 2024-03-25
- 6. From theory to practice: Lessons learned from implementing the Network Sampling with Memory method ArchivedArticles and reports: 11-522-X202200100016Description: To overcome the traditional drawbacks of chain sampling methods, the sampling method called “network sampling with memory” was developed. Its unique feature is to recreate, gradually in the field, a frame for the target population composed of individuals identified by respondents and to randomly draw future respondents from this frame, thereby minimizing selection bias. Tested for the first time in France between September 2020 and June 2021, for a survey among Chinese immigrants in Île-de-France (ChIPRe), this presentation describes the difficulties encountered during collection—sometimes contextual, due to the pandemic, but mostly inherent to the method.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100018Description: The Longitudinal Social Data Development Program (LSDDP) is a social data integration approach aimed at providing longitudinal analytical opportunities without imposing additional burden on respondents. The LSDDP uses a multitude of signals from different data sources for the same individual, which helps to better understand their interactions and track changes over time. This article looks at how the ethnicity status of people in Canada can be estimated at the most detailed disaggregated level possible using the results from a variety of business rules applied to linked data and to the LSDDP denominator. It will then show how improvements were obtained using machine learning methods, such as decision trees and random forest techniques.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100019Description: The purpose of this article is to compare the linkage results for individuals from French tax sources with those of the 2019 Enquête Annuelle de Recensement (EAR), obtained through different methods. Such a comparison will decide whether the Répertoires Statistiques d'Individus et de Logements (Résil) program should be equipped with a probabilistic matching tool for its administrative source identification and matching engine.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100020Description: The reconciliation of 2021 census dwellings with the new Statistical Building Register (SBgR) presented linkage challenges. The Census of Population collected information from various dwelling types. For a large proportion of the population, mailing addresses were at the centre: they were used for reaching out to people and collected as contact info. In parallel, the register environment has been evolving. The agency is transitioning from the Address Register (AR) to the SBgR holding both mailing and location addresses, while also covering non-residential buildings. The reconciliation was conducted using a combination of systems, notably the new Register Matching Engine (RME) for difficult cases. The RME holds an interesting range of sophisticated string comparators. A deterministic linkage approach was used, while incorporating some data knowledge like the entropy. Through metadata, the matching expert could also reduce the amounts of false positives and false negatives.Release date: 2024-03-25
- Articles and reports: 11-633-X2024001Description: The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 35 years.Release date: 2024-01-22
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Reference (7)
Reference (7) ((7 results))
- Surveys and statistical programs – Documentation: 84-538-XGeography: CanadaDescription: This electronic publication presents the methodology underlying the production of the life tables for Canada, provinces and territories.Release date: 2023-08-28
- Surveys and statistical programs – Documentation: 11-633-X2021002Description:
The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 35 years. The IMDB includes Immigration, Refugees and Citizenship Canada (IRCC) administrative records which contain exhaustive information about immigrants who were admitted to Canada since 1952. It also includes data about non-permanent residents who have been issued temporary resident permits since 1980. This report will discuss the IMDB data sources, concepts and variables, record linkage, data processing, dissemination, data evaluation and quality indicators, comparability with other immigration datasets, and the analyses possible with the IMDB.
Release date: 2021-02-01 - Surveys and statistical programs – Documentation: 75F0002M2020001Description:
This note provides the definition of a first-time homebuyer concept used in the 2018 Canadian Housing Survey (CHS). It also includes the methodology used to identify first-time homebuyers and provides sensitivity analysis under alternative methodologies.
Release date: 2020-01-15 - Surveys and statistical programs – Documentation: 11-633-X2018019Description:
The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 30 years. The IMDB combines administrative files on immigrant admissions and non-permanent resident permits from Immigration, Refugees and Citizenship Canada (IRCC) with tax files from the Canadian Revenue Agency (CRA). Information is available for immigrant taxfilers admitted since 1980. Tax records for 1982 and subsequent years are available for immigrant taxfilers. This report will discuss the IMDB data sources, concepts and variables, record linkage, data processing, dissemination, data evaluation and quality indicators, comparability with other immigration datasets, and the analyses possible with the IMDB.
Release date: 2018-12-10 - Surveys and statistical programs – Documentation: 11-633-X2018011Description:
The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 30 years. The IMDB combines administrative files on immigrant admissions and non-permanent resident permits from Immigration, Refugees and Citizenship Canada (IRCC) with tax files from the Canadian Revenue Agency (CRA). Information is available for immigrant taxfilers admitted since 1980. Tax records for 1982 and subsequent years are available for immigrant taxfilers.
This report will discuss the IMDB data sources, concepts and variables, record linkage, data processing, dissemination, data evaluation and quality indicators, comparability with other immigration datasets, and the analyses possible with the IMDB.
Release date: 2018-01-08 - 6. Newsletter for Communities ArchivedNotices and consultations: 11-016-XDescription:
Statistics Canada's Newsletter for Communities offers information to those working for municipal and community organizations about Statistics Canada's data and services. The newsletter also offers links to data releases of the Census and National Household Survey, videos, tutorials, media advisories, learning sessions and presentations.
Release date: 2014-11-20 - Surveys and statistical programs – Documentation: 89-634-X2009008Geography: CanadaDescription:
The Strengths and Difficulties Questionnaire (SDQ) is a parent-reported instrument designed to provide information on children's behaviours and relationships. The SDQ consists of 25 items which are grouped into five subscales: (1) pro-social, (2) inattention-hyperactivity, (3) emotional symptoms, (4) conduct problems, and (5) peer problems. The SDQ was used to provide information on children aged 2 to 5 years in the 2006 Aboriginal Children's Survey (ACS). Though validated on general populations, the constructs of the SDQ have not been validated for off-reserve First Nations, Métis and Inuit children in Canada. The first objective of this evaluation is to examine if the five subscales of the SDQ demonstrate construct validity and reliability for off-reserve First Nations, Métis and Inuit children. The second objective is to examine if an alternative set of subscales, using the 25 SDQ items, may be more valid and reliable for off-reserve First Nations, Métis and Inuit children.
Release date: 2009-11-25
- Date modified: