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All (158) (0 to 10 of 158 results)

1. Bayesian differential privacy for small counties and individual commodities
Articles and reports: 12-001-X202600100011
Description: We construct a hybrid Bayesian method, which includes a differentially private mechanism, to mask Census county totals for a U.S. state on acreage of a commodity. We use surrogates for data collected at the farm level from a past U.S. Census of Agriculture to illustrate our procedure. We use two Bayesian small area models (parametric and mixture) to accommodate the smaller counties with fewer farms and some counties with large acres. In these models, the Laplace distribution provides a differentially private mechanism. In pre-processing, we also incorporate the Census weights to form the observed total acreage, a scaling factor to the Laplace mechanism for each county, a square-root transformation of the observed total acreage to avoid negative masked estimates especially for small counties, and the p-percent rule and the 3+ rule to partition the counties into suppressed counties, non-sensitive counties and sensitive counties. Because of difficulties in specifying and tuning the privacy budget (an unknown parameter), to balance security and utility, we specify a prior for the privacy budget, where the values are not specified, and the Gibbs sampler is used to fit the hierarchical Bayesian models. In post-processing, we use Bayesian predictive inference to obtain masked county acreages, and this includes a benchmarking so that the masked state total matches the observed state total. As a measure of reliability of the Bayesian procedure, we use the posterior coefficients of variation for the masked posterior means of the counties. As a measure of utility, we use the absolute relative errors for the individual counties, together with other global measures. For the sensitive counties, there are some differences between the two small area models but both are much better than an individual area model; the mixture model being the best compromise for security and utility.
Release date: 2026-06-29
2. The early learning and child care industry in Canada: An update to the 2021 report
Articles and reports: 36-28-0001202600600001
Description: This study provides an update to a 2021 report that produced novel estimates of the business characteristics, gross domestic product and business dynamics of child care businesses in Canada through 2016. Administrative data on all tax-filing business in Canada are used to identify incorporated businesses, typically representing child care centres, and unincorporated businesses, typically representing home-based child care businesses without employees.
Release date: 2026-06-24
3. Enhancing the OncoSim-Breast model using Canadian breast density information
Articles and reports: 82-003-X202600500002
Description: Breast cancer is the most commonly diagnosed cancer among women in Canada. Breast density substantially influences breast cancer risk and mammography performance. However, OncoSim-Breast, a Canadian microsimulation model representing breast cancer control, including cancer onset, screening, and survival, has not previously explicitly accounted for breast density. This study describes the incorporation of density-specific parameters—prevalence, relative risk of breast cancer, and digital mammography performance (sensitivity and specificity)—using data from five Canadian provinces, into the OncoSim-Breast model. Calibration experiments and internal validations were conducted to ensure the updated OncoSim-Breast model aligned with observed data from the Canadian Cancer Registry.
Release date: 2026-05-20
4. Preterm births among mothers from racialized groups, 2016-2021
Articles and reports: 82-625-X202600100001
Description: This is a health fact sheet about preterm births among mothers from racialized groups. This analysis includes live births from the five-year period preceding the 2021 Census.
Release date: 2026-05-20
5. Perceived mental health, symptoms of depression and consultations with a mental health professional, Territories, 2023/2024
Articles and reports: 82-625-X202600100002
Description: Perceived mental health, symptoms of depression and consultations with a mental health professional, among adults living in the territories.
Release date: 2026-05-06
6. Performance of hierarchical Bayes small area estimators using noninformative and informative priors with an application to the Canadian Labor Force Survey
Articles and reports: 12-001-X202500200010
Description: In this paper, we study the performance of hierarchical Bayes (HB) small area estimators using noninformative and informative priors. We apply the Bayesian models of You and Chapman (2006) and You (2021) to the Canadian Labor Force Survey (LFS) data and evaluate the impact of the priors on the HB estimators. A Bayesian model comparison and simulation study are also conducted. Our results indicate that a correct informative prior can lead to very good results, and noninformative priors can also perform very well. Incorrect informative priors can lead to poor results in terms of large bias and large coefficient of variation (CV). Noninformative priors are recommended in practice for HB small area estimation unless correctly specified informative priors are available. Informative priors are particularly useful when the number of small areas is relatively small.
Release date: 2025-12-23
7. Regional dynamics of vacancies in health-related occupations in Canada, 2024
Articles and reports: 71-222-X2025003
Description: This article uses annual data from the Job Vacancy and Wage Survey (JVWS) and the Labour Force Survey (LFS) to examine unmet labour demand in 2024 for health care occupations with a focus on specific occupations such as regulated nurses (including registered nurses and registered psychiatric nurses, nurse practitioners, and licensed practical nurses) and personal support workers. It provides an overview of job vacancy trends in healthcare over time in Canada as well as vacancy rates and offered wages for the selected occupations by regional remoteness.
Release date: 2025-12-01
8. The OncoSim-Cervix cancer microsimulation model: Unveiling roll-out strategies for human papillomavirus primary testing
Articles and reports: 82-003-X202501000002
Description: Globally, cervical cancer is one of the most common cancers, yet it is largely preventable. Switching methods for primary screening from cytology testing, via Pap test, to human papillomavirus (HPV) testing is a component of that prevention. OncoSim-Cervix, a Canadian cervical cancer microsimulation model, assesses the long-term effects of HPV vaccination and screening interventions. This study projects the impact of differing roll-out strategies for HPV primary testing for cervical cancer screening in Canada.
Release date: 2025-10-15
9. Improving the Automated Capture of Survey of Household Spending Receipts using advanced Machine Learning Techniques Archived
Articles and reports: 11-522-X202500100004
Description: The Survey of Household Spending (SHS) conducted by Statistics Canada collects paper diaries and shopping receipts as a source of household expenditure data. An auto-capturing algorithm was created for SHS 2023 to reduce statistical clerks' manual work of extracting important information from scanned receipts of common store brands. The algorithm used Tesseract optical character recognition (OCR) to extract text characters from images of receipts, and it identified store and product entities using regular expressions, also known as regex. The goal of this study was to enhance the current auto-capture algorithm by experimenting with more advanced OCR and machine learning methods. As a result, PaddleOCR, an open-source OCR toolkit, was selected as the new default OCR engine due to its overall performance in recognizing texts, especially digits, accurately across receipts of various qualities. Additionally, entity classifiers based on support vector machines were trained on historical SHS records and existing regex patterns. By using classifiers to categorize different elements present on receipts instead of relying solely on regex patterns, product and store recognition improved. It is expected that this new algorithm will be used for SHS 2025 to improve the auto-capture quality and reduce the manual burden associated with capturing receipt variables.
Release date: 2025-09-08
10. Synthetic Data Disclosure Risk Assessment: A Literature Review Archived
Articles and reports: 11-522-X202500100016
Description: The adoption of synthetic data generation as a confidentiality measure is increasing in statistical agencies worldwide, including at Statistics Canada. This approach provides an alternative to the traditional dissemination of anonymized public microdata files, offering both privacy protection and data utility. However, the creation of synthetic data presents challenges in assessing and mitigating disclosure risks. This paper reviews the different types of disclosure risks, that being attribute, membership and identity disclosure, and presents some of the associated methods for measuring risk. The paper presents prominent risk assessment metrics and discusses practical methods for disclosure control in data synthesis. Methods for assessing disclosure risks usually produce a metric that can be used to gauge the risk, but there is little consensus on threshold values for these metrics. It is also important to focus on importance of balancing utility and confidentiality, which needs further discussion in context of these methods. The paper concludes by offering insights and recommendations about managing disclosure risk while creating synthetic data as well as providing some ideas on future directions for research and practical implications for managing disclosure risks in synthetic data.
Release date: 2025-09-08

Stats in brief (14)

Stats in brief (14) (0 to 10 of 14 results)

1. Data ethics part 2: Ethical reviews Archived
Stats in brief: 89-20-00062022004
Description:
Gathering, exploring, analyzing and interpreting data are essential steps in producing information that benefits society, the economy and the environment. In this video, we will discuss the importance of considering data ethics throughout the process of producing statistical information.

As a pre-requisite to this video, make sure to watch the video titled “Data Ethics: An introduction” also available in Statistics Canada’s data literacy training catalogue.

Release date: 2022-10-17
2. Statistics 101: Statistical Bias Archived
Stats in brief: 89-20-00062022005
Description:
In this video, you will learn the answers to the following questions: What are the different types of error? What are the types of error that lead to statistical bias? Where during the data journey statistical bias can occur?

Release date: 2022-10-17
3. Indigenous workers receiving Canada Emergency Response Benefit payments in 2020 Archived
Stats in brief: 45-28-0001202200100007
Description:
This article uses administrative data from the Canada Emergency Response Benefit (CERB) program linked to the 2016 long-form Census to examine socio-economic characteristics of Indigenous workers who received the benefit between March and September 2020. Proportions of workers who received payment are presented by age group, sex, province or region, industry of employment, income and size of business as well as for First Nations, Métis and Inuit workers separately.

Release date: 2022-08-03
4. The outlook of rural businesses, fourth quarter of 2021 Archived
Stats in brief: 45-28-0001202200100001
Description:
This article examines some of the effects of COVID-19 on rural businesses in Canada, with comparison to urban counterparts by industry for contextual support. Topics include business obstacles, expectations for the next year, workforce changes and other subjects from the Canadian Survey on Business Conditions, fourth quarter of 2021.

Release date: 2022-01-12
5. Outlook of rural businesses and impacts related to COVID-19, third quarter of 2021 Archived
Stats in brief: 45-28-0001202100100038
Description:
This article examines some of the effects of COVID-19 on rural businesses in Canada, with comparison to urban counterparts by industry for contextual support. Topics include business obstacles, expectations for the next year, workforce changes and other subjects from the Canadian Survey on Business Conditions, third quarter of 2021.

Release date: 2021-10-18
6. Colorectal cancer screening during the COVID-19 pandemic: Impact of paused screening and evaluation of strategies to reduce delays Archived
Stats in brief: 45-28-0001202100100018
Description: Colorectal cancer screening, along with other health care services, was suspended in Canada in the initial phase of the COVID-19 pandemic response. This pause was deemed necessary to allow health care facilities to establish appropriate infection-control measures to prevent COVID-19 outbreaks and to reserve health system capacity for COVID-19 patients. The current article projects the impact of a three-month suspension of screening for colorectal cancer using a fecal test for average-risk individuals, and compares strategies to minimize the harm from screening interruptions. The projections come from OncoSim, a cancer microsimulation model co-developed by Statistics Canada and the Canadian Partnership Against Cancer.
Release date: 2021-06-17
7. People living in apartments and larger households were at higher risk of dying from COVID-19 during the first wave of the pandemic Archived
Stats in brief: 45-28-0001202100100004
Description:
The risks of mortality due to COVID-19 have been found to be higher for some Canadians (e.g., older population, especially those living in long term care residences, etc.). For Canadians living in close quarters there could also be an increased risk. This article examines the rate of mortality due to COVID-19 associated with people living in different types of private dwellings in Quebec and Ontario. Additionally, the size of the household and the living arrangements are also explored among individuals.
Release date: 2021-04-13
8. Online shopping during the COVID-19 pandemic Archived
Stats in brief: 11-627-M2020088
Description:
Using a custom tabulation of data from the Monthly Retail Trade Survey, this infographic provides a graphical analysis of retail e-commerce vs. in-store sales for selected industries in response to the COVID-19 pandemic.
Release date: 2021-02-05
9. The changes in health and well-being of Canadians with long-term conditions or disabilities since the start of the COVID-19 pandemic Archived
Stats in brief: 45-28-0001202000100082
Description:
This article examines how the self-reported health and mental health of people with long-term health conditions or disabilities has changed since the start of the COVID-19 pandemic explored by age, sex and type of reported difficulty. Additionally, the rates of health service disruptions are explored by type of service and region.

Release date: 2020-10-07
10. COVID-19 Impact Analysis and 2020 Outlook: For-hire Motor Carrier Freight Services Price Index Archived
Stats in brief: 45-28-0001202000100067
Description:
This article presents an impact analysis and 2020 outlook for the For-hire Motor Carrier Freight Services Price Index (FHMCFSPI) amid the COVID-19 pandemic. The FHMCFSPI represents the change in the price of for-hire motor carrier freight services, which are services of goods transportation provided by the trucking industry.
Release date: 2020-08-17

Articles and reports (142)

Articles and reports (142) (0 to 10 of 142 results)

1. Bayesian differential privacy for small counties and individual commodities
Articles and reports: 12-001-X202600100011
Description: We construct a hybrid Bayesian method, which includes a differentially private mechanism, to mask Census county totals for a U.S. state on acreage of a commodity. We use surrogates for data collected at the farm level from a past U.S. Census of Agriculture to illustrate our procedure. We use two Bayesian small area models (parametric and mixture) to accommodate the smaller counties with fewer farms and some counties with large acres. In these models, the Laplace distribution provides a differentially private mechanism. In pre-processing, we also incorporate the Census weights to form the observed total acreage, a scaling factor to the Laplace mechanism for each county, a square-root transformation of the observed total acreage to avoid negative masked estimates especially for small counties, and the p-percent rule and the 3+ rule to partition the counties into suppressed counties, non-sensitive counties and sensitive counties. Because of difficulties in specifying and tuning the privacy budget (an unknown parameter), to balance security and utility, we specify a prior for the privacy budget, where the values are not specified, and the Gibbs sampler is used to fit the hierarchical Bayesian models. In post-processing, we use Bayesian predictive inference to obtain masked county acreages, and this includes a benchmarking so that the masked state total matches the observed state total. As a measure of reliability of the Bayesian procedure, we use the posterior coefficients of variation for the masked posterior means of the counties. As a measure of utility, we use the absolute relative errors for the individual counties, together with other global measures. For the sensitive counties, there are some differences between the two small area models but both are much better than an individual area model; the mixture model being the best compromise for security and utility.
Release date: 2026-06-29
2. The early learning and child care industry in Canada: An update to the 2021 report
Articles and reports: 36-28-0001202600600001
Description: This study provides an update to a 2021 report that produced novel estimates of the business characteristics, gross domestic product and business dynamics of child care businesses in Canada through 2016. Administrative data on all tax-filing business in Canada are used to identify incorporated businesses, typically representing child care centres, and unincorporated businesses, typically representing home-based child care businesses without employees.
Release date: 2026-06-24
3. Enhancing the OncoSim-Breast model using Canadian breast density information
Articles and reports: 82-003-X202600500002
Description: Breast cancer is the most commonly diagnosed cancer among women in Canada. Breast density substantially influences breast cancer risk and mammography performance. However, OncoSim-Breast, a Canadian microsimulation model representing breast cancer control, including cancer onset, screening, and survival, has not previously explicitly accounted for breast density. This study describes the incorporation of density-specific parameters—prevalence, relative risk of breast cancer, and digital mammography performance (sensitivity and specificity)—using data from five Canadian provinces, into the OncoSim-Breast model. Calibration experiments and internal validations were conducted to ensure the updated OncoSim-Breast model aligned with observed data from the Canadian Cancer Registry.
Release date: 2026-05-20
4. Preterm births among mothers from racialized groups, 2016-2021
Articles and reports: 82-625-X202600100001
Description: This is a health fact sheet about preterm births among mothers from racialized groups. This analysis includes live births from the five-year period preceding the 2021 Census.
Release date: 2026-05-20
5. Perceived mental health, symptoms of depression and consultations with a mental health professional, Territories, 2023/2024
Articles and reports: 82-625-X202600100002
Description: Perceived mental health, symptoms of depression and consultations with a mental health professional, among adults living in the territories.
Release date: 2026-05-06
6. Performance of hierarchical Bayes small area estimators using noninformative and informative priors with an application to the Canadian Labor Force Survey
Articles and reports: 12-001-X202500200010
Description: In this paper, we study the performance of hierarchical Bayes (HB) small area estimators using noninformative and informative priors. We apply the Bayesian models of You and Chapman (2006) and You (2021) to the Canadian Labor Force Survey (LFS) data and evaluate the impact of the priors on the HB estimators. A Bayesian model comparison and simulation study are also conducted. Our results indicate that a correct informative prior can lead to very good results, and noninformative priors can also perform very well. Incorrect informative priors can lead to poor results in terms of large bias and large coefficient of variation (CV). Noninformative priors are recommended in practice for HB small area estimation unless correctly specified informative priors are available. Informative priors are particularly useful when the number of small areas is relatively small.
Release date: 2025-12-23
7. Regional dynamics of vacancies in health-related occupations in Canada, 2024
Articles and reports: 71-222-X2025003
Description: This article uses annual data from the Job Vacancy and Wage Survey (JVWS) and the Labour Force Survey (LFS) to examine unmet labour demand in 2024 for health care occupations with a focus on specific occupations such as regulated nurses (including registered nurses and registered psychiatric nurses, nurse practitioners, and licensed practical nurses) and personal support workers. It provides an overview of job vacancy trends in healthcare over time in Canada as well as vacancy rates and offered wages for the selected occupations by regional remoteness.
Release date: 2025-12-01
8. The OncoSim-Cervix cancer microsimulation model: Unveiling roll-out strategies for human papillomavirus primary testing
Articles and reports: 82-003-X202501000002
Description: Globally, cervical cancer is one of the most common cancers, yet it is largely preventable. Switching methods for primary screening from cytology testing, via Pap test, to human papillomavirus (HPV) testing is a component of that prevention. OncoSim-Cervix, a Canadian cervical cancer microsimulation model, assesses the long-term effects of HPV vaccination and screening interventions. This study projects the impact of differing roll-out strategies for HPV primary testing for cervical cancer screening in Canada.
Release date: 2025-10-15
9. Improving the Automated Capture of Survey of Household Spending Receipts using advanced Machine Learning Techniques Archived
Articles and reports: 11-522-X202500100004
Description: The Survey of Household Spending (SHS) conducted by Statistics Canada collects paper diaries and shopping receipts as a source of household expenditure data. An auto-capturing algorithm was created for SHS 2023 to reduce statistical clerks' manual work of extracting important information from scanned receipts of common store brands. The algorithm used Tesseract optical character recognition (OCR) to extract text characters from images of receipts, and it identified store and product entities using regular expressions, also known as regex. The goal of this study was to enhance the current auto-capture algorithm by experimenting with more advanced OCR and machine learning methods. As a result, PaddleOCR, an open-source OCR toolkit, was selected as the new default OCR engine due to its overall performance in recognizing texts, especially digits, accurately across receipts of various qualities. Additionally, entity classifiers based on support vector machines were trained on historical SHS records and existing regex patterns. By using classifiers to categorize different elements present on receipts instead of relying solely on regex patterns, product and store recognition improved. It is expected that this new algorithm will be used for SHS 2025 to improve the auto-capture quality and reduce the manual burden associated with capturing receipt variables.
Release date: 2025-09-08
10. Synthetic Data Disclosure Risk Assessment: A Literature Review Archived
Articles and reports: 11-522-X202500100016
Description: The adoption of synthetic data generation as a confidentiality measure is increasing in statistical agencies worldwide, including at Statistics Canada. This approach provides an alternative to the traditional dissemination of anonymized public microdata files, offering both privacy protection and data utility. However, the creation of synthetic data presents challenges in assessing and mitigating disclosure risks. This paper reviews the different types of disclosure risks, that being attribute, membership and identity disclosure, and presents some of the associated methods for measuring risk. The paper presents prominent risk assessment metrics and discusses practical methods for disclosure control in data synthesis. Methods for assessing disclosure risks usually produce a metric that can be used to gauge the risk, but there is little consensus on threshold values for these metrics. It is also important to focus on importance of balancing utility and confidentiality, which needs further discussion in context of these methods. The paper concludes by offering insights and recommendations about managing disclosure risk while creating synthetic data as well as providing some ideas on future directions for research and practical implications for managing disclosure risks in synthetic data.
Release date: 2025-09-08

Journals and periodicals (2)

Journals and periodicals (2) ((2 results))

1. Gross Domestic Product by Industry: Sources and Methods with Industry Details Archived
Journals and periodicals: 15-548-X
Description:
This document describes all aspects of output-based Gross Domestic Product (GDP), also known as GDP by industry or simply monthly GDP. It contains a comprehensive record of specific methodologies and data sources, on an industry by industry basis.
It is meant to complement a previous Statistics Canada publication, released in November 2002, entitled Gross Domestic Product by Industry, Sources and Methods (Catalogue no. 15-547), which discusses in general terms the concepts, definitions, classifications and statistical methods underlying the monthly GDP measures.
Release date: 2006-02-28
2. From Home to School - How Canadian Children Cope Archived
Journals and periodicals: 89F0117X
Geography: Canada
Description:
This report outlines some initial results from the School Component of the first and second cycles of the National Longitudinal Survey of Children and Youth (NLSCY). It examines the longitudinal influence of Early Childhood Care and Education and literacy activities on young children's future academic and cognitive outcomes. This overview highlights the information newly available from this component of the survey; it is not comprehensive in its coverage or its analysis. Indeed, the information collected by the NLSCY is so rich and detailed that researchers and analysts will be using it to address a variety of important questions concerning the education of children and youth in Canada for many years to come. Here then, we are merely scratching the surface to stimulate awareness of this rich new data source, and to illustrate the kinds of analyses it makes possible.
Release date: 1999-10-14

Date modified:: 2026-08-15

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