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Results
All (30)
All (30) (0 to 10 of 30 results)
- Articles and reports: 82-003-X202101100001Description:
The fitness levels of Canadian adults declined substantially between 1981 and the years 2007 to 2009, suggesting a reduction in population health. This paper updates the fitness trends of Canadians aged 20 to 69 years by extending the time period to 2017.
Release date: 2021-11-17 - 2. Construction of a Northern Market Basket Measure of poverty for Yukon and the Northwest TerritoriesArticles and reports: 75F0002M2021007Description:
This discussion paper describes the proposed methodology for a Northern Market Basket Measure (MBM-N) for Yukon and the Northwest Territories, as well as identifies research which could be conducted in preparation for the 2023 review. The paper presents initial MBM-N thresholds and provides preliminary poverty estimates for reference years 2018 and 2019. A review period will follow the release of this paper, during which time Statistics Canada and Employment and Social Development Canada will welcome feedback from interested parties and work with experts, stakeholders, indigenous organizations, federal, provincial and territorial officials to validate the results.
Release date: 2021-11-12 - Articles and reports: 11-522-X202100100029Description:
In line with the path taken by the European Statistical System, Istat is investing on innovative methods to harness Big Data sources and to use them for the production of new and enriched Official Statistics products. Big Data sources are not, in general, directly tractable with traditional statistical techniques, just think of specific data types such as images and texts that are examples of the Variety dimension of Big Data. This motivates and justifies the growing interest of National Statistical Institutes in data science techniques. Istat is currently using data science techniques, including machine learning techniques, in innovation projects and for the publication of experimental statistics. This paper will provide an overview of the main current projects by Istat and will focus on two specific Big Data-based production pipelines, related to the processing of respectively text sources and imagery sources. The paper will highlight the main challenges these two pipelines and the solutions put in place to solve them.
Key Words: Machine Learning; Text Processing; Image Processing; Big Data
Release date: 2021-11-05 - Articles and reports: 11-522-X202100100008Description:
Non-probability samples are being increasingly explored by National Statistical Offices as a complement to probability samples. We consider the scenario where the variable of interest and auxiliary variables are observed in both a probability and non-probability sample. Our objective is to use data from the non-probability sample to improve the efficiency of survey-weighted estimates obtained from the probability sample. Recently, Sakshaug, Wisniowski, Ruiz and Blom (2019) and Wisniowski, Sakshaug, Ruiz and Blom (2020) proposed a Bayesian approach to integrating data from both samples for the estimation of model parameters. In their approach, non-probability sample data are used to determine the prior distribution of model parameters, and the posterior distribution is obtained under the assumption that the probability sampling design is ignorable (or not informative). We extend this Bayesian approach to the prediction of finite population parameters under non-ignorable (or informative) sampling by conditioning on appropriate survey-weighted statistics. We illustrate the properties of our predictor through a simulation study.
Key Words: Bayesian prediction; Gibbs sampling; Non-ignorable sampling; Statistical data integration.
Release date: 2021-10-29 - Articles and reports: 11-522-X202100100005Description: The Permanent Census of Population and Housing is the new census strategy adopted in Italy in 2018: it is based on statistical registers combined with data collected through surveys specifically designed to improve registers quality and assure Census outputs. The register at the core of the Permanent Census is the Population Base Register (PBR), whose main administrative sources are the Local Population Registers. The population counts are determined correcting the PBR data with coefficients based on the coverage errors estimated with surveys data, but the need for additional administrative sources clearly emerged while processing the data collected with the first round of Permanent Census. The suspension of surveys due to global-pandemic emergency, together with a serious reduction in census budget for next years, makes more urgent a change in estimation process so to use administrative data as the main source. A thematic register has been set up to exploit all the additional administrative sources: knowledge discovery from this database is essential to extract relevant patterns and to build new dimensions called signs of life, useful for population estimation. The availability of the collected data of the two first waves of Census offers a unique and valuable set for statistical learning: association between surveys results and ‘signs of life’ could be used to build classification model to predict coverage errors in PBR. This paper present the results of the process to produce ‘signs of life’ that proved to be significant in population estimation.
Key Words: Administrative data; Population Census; Statistical Registers; Knowledge discovery from databases.
Release date: 2021-10-22 - 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 - Articles and reports: 11-522-X202100100007Description: The National Center for Health Statistics (NCHS) annually administers the National Ambulatory Medical Care Survey (NAMCS) to assess practice characteristics and ambulatory care provided by office-based physicians in the United States, including interviews with sampled physicians. After the onset of the COVID-19 pandemic, NCHS adapted NAMCS methodology to assess the impacts of COVID-19 on office-based physicians, including: shortages of personal protective equipment; COVID-19 testing in physician offices; providers testing positive for COVID-19; and telemedicine use during the pandemic. This paper describes challenges and opportunities in administering the 2020 NAMCS and presents key findings regarding physician experiences during the COVID-19 pandemic.
Key Words: National Ambulatory Medical Care Survey (NAMCS); Office-based physicians; Telemedicine; Personal protective equipment.
Release date: 2021-10-22 - Articles and reports: 11-522-X202100100017Description: The outbreak of the COVID-19 pandemic required the Government of Canada to provide relevant and timely information to support decision-making around a host of issues, including personal protective equipment (PPE) procurement and deployment. Our team built a compartmental epidemiological model from an existing code base to project PPE demand under a range of epidemiological scenarios. This model was further enhanced using data science techniques, which allowed for the rapid development and dissemination of model results to inform policy decisions.
Key Words: COVID-19; SARS-CoV-2; Epidemiological model; Data science; Personal Protective Equipment (PPE); SEIR
Release date: 2021-10-22 - Articles and reports: 36-28-0001202100900002Description:
In Canada, the gender wage gap continues to persist and nearly two-thirds of the gap was still unexplained by standard factors such as level of education, job attributes, proportions of women and men in higher-paying occupations or industries, and demographics. This points to a continued need for analysis in this area in order to better understand gender-based wage disparity, including gender-related biases in career advancement. Using new content developed in the 2016 General Social Survey (GSS Cycle 30): Canadians at Work and Home, this study investigates the possible existence and magnitude of gender-related biases in career advancement that may prevent women from advancing in their careers.
Release date: 2021-09-22 - Articles and reports: 36-28-0001202100900004Description:
In recent decades, women’s educational attainment has increased significantly in Canada. In 2016, 40.7% of young women aged 25 to 34 reported having a bachelor's degree or higher, up from 32.8% in 2006. By comparison, 29.1% of young men aged 25 to 34 reported having a bachelor's degree or higher, up from 24.8% in 2006. This short study discusses gender-based differences in desired level of educational attainment for students, as well as obstacles encountered in school.
Release date: 2021-09-22
Stats in brief (5)
Stats in brief (5) ((5 results))
- 1. Canadians online in 2020 ArchivedStats in brief: 11-627-M2021049Description:
The 2020 Canadian Internet Use Survey (CIUS) measures the impact of digital technologies on the lives of Canadians, including how individuals access and use the Internet, their intensity of use, demand for certain online activities, and interactions online as well as the changes in use of digital tech as a result of COVID-19. This infographic examines Canadians use of the Internet and digital technologies as well as certain online activities done for the first time during COVID-19.
Release date: 2021-09-07 - Stats in brief: 11-627-M2021048Description:
The 2020 Canadian Internet Use Survey (CIUS) measures the impact of digital technologies on the lives of Canadians, including how individuals access and use the Internet, their intensity of use, demand for certain online activities such as e-commerce and barriers to shopping online. This infographic examines what Canadians have reported about their online spending behaviours.
Release date: 2021-06-22 - Stats in brief: 11-627-M2021045Description:
The infographic shows the percentage of Canadian businesses by region that required personal protective equipment (PPE) over the last three iterations of the survey (October 2020, December 2020, and February 2021). It also presents estimates of demand for various PPE items by region for February 2021.
Release date: 2021-04-23 - Stats in brief: 11-627-M2021008Description:
Drawn from publicly available data contained in the Canadian Civil Aircraft Register Database, this infographic presents summary data on commercial aircraft registrations in Canada. The infographic was prepared by Statistics Canada in collaboration with Transport Canada.
Release date: 2021-03-04 - Stats in brief: 11-627-M2021009Description:
Drawn from publicly available data contained in the Canadian Civil Aircraft Register Database, this infographic presents summary data on private aircraft registrations in Canada. The infographic was prepared by Statistics Canada, in collaboration with Transport Canada.
Release date: 2021-03-04
Articles and reports (25)
Articles and reports (25) (0 to 10 of 25 results)
- Articles and reports: 82-003-X202101100001Description:
The fitness levels of Canadian adults declined substantially between 1981 and the years 2007 to 2009, suggesting a reduction in population health. This paper updates the fitness trends of Canadians aged 20 to 69 years by extending the time period to 2017.
Release date: 2021-11-17 - 2. Construction of a Northern Market Basket Measure of poverty for Yukon and the Northwest TerritoriesArticles and reports: 75F0002M2021007Description:
This discussion paper describes the proposed methodology for a Northern Market Basket Measure (MBM-N) for Yukon and the Northwest Territories, as well as identifies research which could be conducted in preparation for the 2023 review. The paper presents initial MBM-N thresholds and provides preliminary poverty estimates for reference years 2018 and 2019. A review period will follow the release of this paper, during which time Statistics Canada and Employment and Social Development Canada will welcome feedback from interested parties and work with experts, stakeholders, indigenous organizations, federal, provincial and territorial officials to validate the results.
Release date: 2021-11-12 - Articles and reports: 11-522-X202100100029Description:
In line with the path taken by the European Statistical System, Istat is investing on innovative methods to harness Big Data sources and to use them for the production of new and enriched Official Statistics products. Big Data sources are not, in general, directly tractable with traditional statistical techniques, just think of specific data types such as images and texts that are examples of the Variety dimension of Big Data. This motivates and justifies the growing interest of National Statistical Institutes in data science techniques. Istat is currently using data science techniques, including machine learning techniques, in innovation projects and for the publication of experimental statistics. This paper will provide an overview of the main current projects by Istat and will focus on two specific Big Data-based production pipelines, related to the processing of respectively text sources and imagery sources. The paper will highlight the main challenges these two pipelines and the solutions put in place to solve them.
Key Words: Machine Learning; Text Processing; Image Processing; Big Data
Release date: 2021-11-05 - Articles and reports: 11-522-X202100100008Description:
Non-probability samples are being increasingly explored by National Statistical Offices as a complement to probability samples. We consider the scenario where the variable of interest and auxiliary variables are observed in both a probability and non-probability sample. Our objective is to use data from the non-probability sample to improve the efficiency of survey-weighted estimates obtained from the probability sample. Recently, Sakshaug, Wisniowski, Ruiz and Blom (2019) and Wisniowski, Sakshaug, Ruiz and Blom (2020) proposed a Bayesian approach to integrating data from both samples for the estimation of model parameters. In their approach, non-probability sample data are used to determine the prior distribution of model parameters, and the posterior distribution is obtained under the assumption that the probability sampling design is ignorable (or not informative). We extend this Bayesian approach to the prediction of finite population parameters under non-ignorable (or informative) sampling by conditioning on appropriate survey-weighted statistics. We illustrate the properties of our predictor through a simulation study.
Key Words: Bayesian prediction; Gibbs sampling; Non-ignorable sampling; Statistical data integration.
Release date: 2021-10-29 - Articles and reports: 11-522-X202100100005Description: The Permanent Census of Population and Housing is the new census strategy adopted in Italy in 2018: it is based on statistical registers combined with data collected through surveys specifically designed to improve registers quality and assure Census outputs. The register at the core of the Permanent Census is the Population Base Register (PBR), whose main administrative sources are the Local Population Registers. The population counts are determined correcting the PBR data with coefficients based on the coverage errors estimated with surveys data, but the need for additional administrative sources clearly emerged while processing the data collected with the first round of Permanent Census. The suspension of surveys due to global-pandemic emergency, together with a serious reduction in census budget for next years, makes more urgent a change in estimation process so to use administrative data as the main source. A thematic register has been set up to exploit all the additional administrative sources: knowledge discovery from this database is essential to extract relevant patterns and to build new dimensions called signs of life, useful for population estimation. The availability of the collected data of the two first waves of Census offers a unique and valuable set for statistical learning: association between surveys results and ‘signs of life’ could be used to build classification model to predict coverage errors in PBR. This paper present the results of the process to produce ‘signs of life’ that proved to be significant in population estimation.
Key Words: Administrative data; Population Census; Statistical Registers; Knowledge discovery from databases.
Release date: 2021-10-22 - 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 - Articles and reports: 11-522-X202100100007Description: The National Center for Health Statistics (NCHS) annually administers the National Ambulatory Medical Care Survey (NAMCS) to assess practice characteristics and ambulatory care provided by office-based physicians in the United States, including interviews with sampled physicians. After the onset of the COVID-19 pandemic, NCHS adapted NAMCS methodology to assess the impacts of COVID-19 on office-based physicians, including: shortages of personal protective equipment; COVID-19 testing in physician offices; providers testing positive for COVID-19; and telemedicine use during the pandemic. This paper describes challenges and opportunities in administering the 2020 NAMCS and presents key findings regarding physician experiences during the COVID-19 pandemic.
Key Words: National Ambulatory Medical Care Survey (NAMCS); Office-based physicians; Telemedicine; Personal protective equipment.
Release date: 2021-10-22 - Articles and reports: 11-522-X202100100017Description: The outbreak of the COVID-19 pandemic required the Government of Canada to provide relevant and timely information to support decision-making around a host of issues, including personal protective equipment (PPE) procurement and deployment. Our team built a compartmental epidemiological model from an existing code base to project PPE demand under a range of epidemiological scenarios. This model was further enhanced using data science techniques, which allowed for the rapid development and dissemination of model results to inform policy decisions.
Key Words: COVID-19; SARS-CoV-2; Epidemiological model; Data science; Personal Protective Equipment (PPE); SEIR
Release date: 2021-10-22 - Articles and reports: 36-28-0001202100900002Description:
In Canada, the gender wage gap continues to persist and nearly two-thirds of the gap was still unexplained by standard factors such as level of education, job attributes, proportions of women and men in higher-paying occupations or industries, and demographics. This points to a continued need for analysis in this area in order to better understand gender-based wage disparity, including gender-related biases in career advancement. Using new content developed in the 2016 General Social Survey (GSS Cycle 30): Canadians at Work and Home, this study investigates the possible existence and magnitude of gender-related biases in career advancement that may prevent women from advancing in their careers.
Release date: 2021-09-22 - Articles and reports: 36-28-0001202100900004Description:
In recent decades, women’s educational attainment has increased significantly in Canada. In 2016, 40.7% of young women aged 25 to 34 reported having a bachelor's degree or higher, up from 32.8% in 2006. By comparison, 29.1% of young men aged 25 to 34 reported having a bachelor's degree or higher, up from 24.8% in 2006. This short study discusses gender-based differences in desired level of educational attainment for students, as well as obstacles encountered in school.
Release date: 2021-09-22
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