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All (563) (0 to 10 of 563 results)

1. Statistics Canada: Departmental Sustainable Development Strategy, 2023 to 2027
Journals and periodicals: 45-26-0001
Description: The Departmental Sustainable Development Strategy (DSDS) outlines departmental actions, with measurable performance indicators, that support the implementation strategies of the 2022-2026 Federal Sustainable Development Strategy. The DSDS further outlines Statistics Canada’s sustainable development vision to produce data to help track whether Canada is moving toward a more sustainable future and highlights projects with links to supporting sustainable development goals.
Release date: 2024-12-27
2. Statistics Canada: Road to Accessibility
Articles and reports: 13-26-0004
Description: StatCan's accessibility plan aims to ensure that all StatCan and Statistical Survey Operations employees are supported in a barrier-free environment, with their accessibility needs met. Statistics Canada: Road to Accessibility 2023-25 is intended to be evergreen. As we make progress toward achieving an accessible and inclusive StatCan, our actions and commitments will change and evolve, and the Plan will be updated to ensure a continued and relevant focus on the areas needing it most.
Release date: 2024-12-20
3. Exploring a skewness conjecture: Expanding Cochran’s rule to a proportion estimated from a complex sample
Articles and reports: 12-001-X202400200001
Description: Cochran’s rule states that a standard (Wald) two-sided 95% confidence interval around a sample mean drawn from a population with positive skewness is reasonable when the sample size is greater than 25 times the square of the skewness coefficient of the population. We investigate whether a variant of this crude rule applies for a proportion estimated from a stratified simple random sample.
Release date: 2024-12-20
4. Daily rhythm of data quality: Evidence from the Survey of Unemployed Workers in New Jersey
Articles and reports: 12-001-X202400200002
Description: This paper investigates whether survey data quality fluctuates over the day. After laying out the argument theoretically, panel data from the Survey of Unemployed Workers in New Jersey are analyzed. Several indirect indicators of response error are investigated, including item nonresponse, interview completion time, rounding, and measures of the quality of time diary data. The evidence that we assemble for a time of day of interview effect is weak or nonexistent. Item nonresponse and the probability that interview completion time is among the 5% shortest appear to increase in the evening, but a more thorough assessment requires instrumental variables.
Release date: 2024-12-20
5. Recursive Neyman algorithm for optimum sample allocation under box constraints on sample sizes in strata
Articles and reports: 12-001-X202400200003
Description: The optimum sample allocation in stratified sampling is one of the basic issues of survey methodology. It is a procedure of dividing the overall sample size into strata sample sizes in such a way that for given sampling designs in strata the variance of the stratified \pi estimator of the population total (or mean) for a given study variable assumes its minimum. In this work, we consider the optimum allocation of a sample, under lower and upper bounds imposed jointly on sample sizes in strata. We are concerned with the variance function of some generic form that, in particular, covers the case of the simple random sampling without replacement in strata. The goal of this paper is twofold. First, we establish (using the Karush-Kuhn-Tucker conditions) a generic form of the optimal solution, the so-called optimality conditions. Second, based on the established optimality conditions, we derive an efficient recursive algorithm, named RNABOX, which solves the allocation problem under study. The RNABOX can be viewed as a generalization of the classical recursive Neyman allocation algorithm, a popular tool for optimum allocation when only upper bounds are imposed on sample strata-sizes. We implement RNABOX in R as a part of our package stratallo which is available from the Comprehensive R Archive Network (CRAN) repository.
Release date: 2024-12-20
6. Bayesian predictive inference of a finite population mean without specifying the relation between the study variable and the covariates
Articles and reports: 12-001-X202400200004
Description: While we avoid specifying the parametric relationship between the study variable and covariates, we illustrate the advantage of including a spatial component to better account for the covariates in our models to make Bayesian predictive inference. We treat each unique covariate combination as an individual stratum, then we use small area estimation techniques to make inference about the finite population mean of the continuous response variable. The two spatial models used are the conditional autoregressive and simple conditional autoregressive models. We include the spatial effects by creating the adjacency matrix via the Mahalanobis distance between covariates. We also show how to incorporate survey weights into the spatial models when dealing with probability survey data. We compare the results of two non-spatial models including the Scott-Smith model and the Battese, Harter, and Fuller model to the spatial models. We illustrate the comparison between the aforementioned models with an application using BMI data from eight counties in California. Our goal is to have neighboring strata yield similar predictions, and to increase the difference between strata that are not neighbors. Ultimately, using the spatial models shows less global pooling compared to the non-spatial models, which was the desired outcome.
Release date: 2024-12-20
7. Robust adaptive survey design for time changes in mixed-mode response propensities
Articles and reports: 12-001-X202400200005
Description: Adaptive survey designs (ASDs) tailor recruitment protocols to population subgroups that are relevant to a survey. In recent years, effective ASD optimization has been the topic of research and several applications. However, the performance of an optimized ASD over time is sensitive to time changes in response propensities. How adaptation strategies can adjust to such variation over time is not yet fully understood. In this paper, we propose a robust optimization approach in the context of sequential mixed-mode surveys employing Bayesian analysis. The approach is formulated as a mathematical programming problem that explicitly accounts for uncertainty due to time change. ASD decisions can then be made by considering time-dependent variation in conditional mode response propensities and between-mode correlations in response propensities. The approach is demonstrated using a case study: the 2014-2017 Dutch Health Survey. We evaluate the sensitivity of ASD performance to 1) the budget level and 2) the length of applicable historic time-series data. We find there is only a moderate dependence on the budget level and the dependence on historic data is moderated by the amount of seasonality during the year.
Release date: 2024-12-20
8. Investigating mode effects in interviewer variances using two representative multi-mode surveys
Articles and reports: 12-001-X202400200006
Description: As mixed-mode designs become increasingly popular, their effects on data quality have attracted much scholarly attention. Most studies focused on the bias properties of mixed-mode designs; few of them have investigated whether mixed-mode designs have heterogeneous variance structures across modes. While many characteristics of mixed-mode designs, such as varied interviewer usage, systematic differences in respondents, varying levels of social desirability bias, among others, may lead to heterogeneous variances in mode-specific point estimates of population means, this study specifically investigates whether interviewer variances remain consistent across different modes in mixed-mode studies. To address this research question, we utilize data collected from two distinct study designs. In the first design, when interviewers are responsible for either face-to-face or telephone mode, we examine whether there are mode differences in interviewer variances for 1) sensitive political questions, 2) international items, 3) and item missing indicators on international items, using the Arab Barometer wave 6 Jordan data. In the second design, we draw on Health and Retirement Study (HRS) 2016 core survey data to examine the question on three topics when interviewers are responsible for both modes. The topics cover 1) the CESD depression scale, 2) interviewer observations, and 3) the physical activity scale. To account for the lack of interpenetrated designs in both data sources, we include respondent-level covariates in our models. We find significant differences in interviewer variances on one item (twelve items in total) in the Arab Barometer study; whereas for HRS, the results are three out of eighteen. Overall, we find the magnitude of the interviewer variances larger in FTF than TEL on sensitive items. We conduct simulations to understand the power to detect mode effects in the typically modest interviewer sample sizes.
Release date: 2024-12-20
9. Models of linkage error for capture-recapture estimation without clerical reviews
Articles and reports: 12-001-X202400200007
Description: The capture-recapture method can be applied to measure the coverage of administrative and big data sources, in official statistics. In its basic form, it involves the linkage of two sources while assuming a perfect linkage and other standard assumptions. In practice, linkage errors arise and are a potential source of bias, where the linkage is based on quasi-identifiers. These errors include false positives and false negatives, where the former arise when linking a pair of records from different units, and the latter arise when not linking a pair of records from the same unit. So far, the existing solutions have resorted to costly clerical reviews, or they have made the restrictive conditional independence assumption. In this work, these requirements are relaxed by modeling the number of links from a record instead. The same approach may be taken to estimate the linkage accuracy without clerical reviews, when linking two sources that each have some undercoverage.
Release date: 2024-12-20
10. Fully synthetic data for complex surveys
Articles and reports: 12-001-X202400200008
Description: When seeking to release public use files for confidential data, statistical agencies can generate fully synthetic data. We propose an approach for making fully synthetic data from surveys collected with complex sampling designs. Our approach adheres to the general strategy proposed by Rubin (1993). Specifically, we generate pseudo-populations by applying the weighted finite population Bayesian bootstrap to account for survey weights, take simple random samples from those pseudo-populations, estimate synthesis models using these simple random samples, and release simulated data drawn from the models as public use files. To facilitate variance estimation, we use the framework of multiple imputation with two data generation strategies. In the first, we generate multiple data sets from each simple random sample. In the second, we generate a single synthetic data set from each simple random sample. We present multiple imputation combining rules for each setting. We illustrate the repeated sampling properties of the combining rules via simulation studies, including comparisons with synthetic data generation based on pseudo-likelihood methods. We apply the proposed methods to a subset of data from the American Community Survey.
Release date: 2024-12-20

Data (103)

Data (103) (0 to 10 of 103 results)

1. National Address Register
Profile of a community or region: 46-26-0002
Description: The National Address Register (NAR) is a list of commercial and residential addresses in Canada that are extracted from Statistics Canada's Building Register and deemed non-confidential.
Release date: 2024-12-20
2. Gross Domestic Product and trade in Canada's environmental and clean technology products sector
Data Visualization: 71-607-X2023015
Description: This interactive dashboard provides access to current and historical gross domestic product (GDP) and international trade values in Canada's environmental and clean technology products sector. With its interactive map and charts, it allows the user to compare and analyze this sector's GDP, imports and exports by province and territory and by product.
This web-based application is updated annually, once the data for the latest reference period is released in The Daily.
Release date: 2024-12-20
3. Employment and compensation of employees in Canada's environmental and clean technology products sector
Data Visualization: 71-607-X2023016
Description: This interactive dashboard provides access to current and historical employment and compensation of employees' data in Canada's environmental and clean technology products sector. With its interactive map and charts it allows the user to compare and analyze provincial and territorial job and average annual compensation estimates, by product and by industry.
This web-based application is updated annually, once the data for the latest reference period is released in The Daily.
Release date: 2024-12-20
4. Energy use and greenhouse gas emissions associated with various aspects of the Canadian economy
Data Visualization: 71-607-X2024016
Description: The production of goods and the delivery of services result in energy use and greenhouse gas (GHG) emissions. This visualization provides insights into the relationship between Canadian economic activity and the environment by including estimates of Canadian GHG emissions and energy use.
Release date: 2024-12-20
5. Longitudinal Immigration Database (IMDB) Interactive Application: Mobility
Data Visualization: 71-607-X2019033
Description: Immigrant Mobility by Geography of admission, Geography of residence, Immigrant mobility indicators, Age groups and sex at taxation year, Pre-admission experience, Knowledge of official languages at admission, Immigrant admission category, and admission year.
Release date: 2024-12-19
6. Employment Insurance Beneficiaries in Rural and Small Town Canada: Interactive Dashboard
Data Visualization: 71-607-X2024011
Description: This dashboard is designed for users to explore current and historical counts of employment insurance beneficiaries by geography, age group, sex, and beneficiary details. This web-based application undergoes monthly updates.
Release date: 2024-12-18
7. Canada's population clock (real-time model)
Data Visualization: 71-607-X2018005
Description: This data visualization product provides information on the pace of population renewal in Canada. The web page shows a real-time model of population growth in Canada. The components of population growth are modelled in order to adjust the population of the country, provinces and territories. Moreover, a map is showing in which provinces and territories the demographic events are occurring.

Data modelled in real time on this web page are not to be confused with Census counts and demographic estimates, which are the measures used to determine the size of the population in the context of various governmental programs.
Release date: 2024-12-17
8. Wholesale and Retail Services Price Indexes: Interactive Tool
Data Visualization: 71-607-X2019015
Description: This dashboard highlights the latest data for the Wholesale Services Price Index (WSPI) and the Retail Services Price Index (RSPI). The WSPI and the RSPI are indicators of change in the price of wholesaling and retailing services in Canada. This price is defined as a margin, which is the difference between the selling price and the purchase price of products sold. With this tool, data users can explore current and historical trends for various types of wholesaling and retailing services. Key indicators such as the latest quarterly and year-over-year (annual) changes, as well as services price trends are presented in interactive charts, allowing users to compare and analyze services price changes over time for different types of services. The interactive tool also allows users to rank subsectors based on their relative importance (2013 weights) to the overall Canadian wholesale or retail sector . This web-based application is updated quarterly, as soon as data for the latest reference period are released in The Daily.
Release date: 2024-12-17
9. Quarterly demographic estimates, provinces and territories: Interactive dashboard
Data Visualization: 71-607-X2019036
Description: This interactive dashboard allows the user to visualize the factors of Canada's population growth and how they have changed over time for Canada, the provinces and territories. Statistics for the most recent quarter are also presented. The dashboard shows population, population growth, population weight, and factors of population growth (natural increase, international migration, interprovincial migration). The user can view the data for Canada or by selecting a province or territory of interest.
Release date: 2024-12-17
10. The Open Database of Educational Facilities
Table: 37-26-0001
Description: The Open Database of Educational Facilities (ODEF) is a compilation of data from open and internet sources on the locations and types of educational facilities across Canada, originating from municipal, regional, and provincial governments. It is a centralized and harmonized repository of educational facility data made available under the Open Government License - Canada. The database is expected to be updated periodically as new open datasets from government sources become available. The database is made available for download as a zipped comma separated values (csv) file.
Release date: 2024-12-13

Analysis (410)

Analysis (410) (0 to 10 of 410 results)

1. Statistics Canada: Departmental Sustainable Development Strategy, 2023 to 2027
Journals and periodicals: 45-26-0001
Description: The Departmental Sustainable Development Strategy (DSDS) outlines departmental actions, with measurable performance indicators, that support the implementation strategies of the 2022-2026 Federal Sustainable Development Strategy. The DSDS further outlines Statistics Canada’s sustainable development vision to produce data to help track whether Canada is moving toward a more sustainable future and highlights projects with links to supporting sustainable development goals.
Release date: 2024-12-27
2. Statistics Canada: Road to Accessibility
Articles and reports: 13-26-0004
Description: StatCan's accessibility plan aims to ensure that all StatCan and Statistical Survey Operations employees are supported in a barrier-free environment, with their accessibility needs met. Statistics Canada: Road to Accessibility 2023-25 is intended to be evergreen. As we make progress toward achieving an accessible and inclusive StatCan, our actions and commitments will change and evolve, and the Plan will be updated to ensure a continued and relevant focus on the areas needing it most.
Release date: 2024-12-20
3. Exploring a skewness conjecture: Expanding Cochran’s rule to a proportion estimated from a complex sample
Articles and reports: 12-001-X202400200001
Description: Cochran’s rule states that a standard (Wald) two-sided 95% confidence interval around a sample mean drawn from a population with positive skewness is reasonable when the sample size is greater than 25 times the square of the skewness coefficient of the population. We investigate whether a variant of this crude rule applies for a proportion estimated from a stratified simple random sample.
Release date: 2024-12-20
4. Daily rhythm of data quality: Evidence from the Survey of Unemployed Workers in New Jersey
Articles and reports: 12-001-X202400200002
Description: This paper investigates whether survey data quality fluctuates over the day. After laying out the argument theoretically, panel data from the Survey of Unemployed Workers in New Jersey are analyzed. Several indirect indicators of response error are investigated, including item nonresponse, interview completion time, rounding, and measures of the quality of time diary data. The evidence that we assemble for a time of day of interview effect is weak or nonexistent. Item nonresponse and the probability that interview completion time is among the 5% shortest appear to increase in the evening, but a more thorough assessment requires instrumental variables.
Release date: 2024-12-20
5. Recursive Neyman algorithm for optimum sample allocation under box constraints on sample sizes in strata
Articles and reports: 12-001-X202400200003
Description: The optimum sample allocation in stratified sampling is one of the basic issues of survey methodology. It is a procedure of dividing the overall sample size into strata sample sizes in such a way that for given sampling designs in strata the variance of the stratified \pi estimator of the population total (or mean) for a given study variable assumes its minimum. In this work, we consider the optimum allocation of a sample, under lower and upper bounds imposed jointly on sample sizes in strata. We are concerned with the variance function of some generic form that, in particular, covers the case of the simple random sampling without replacement in strata. The goal of this paper is twofold. First, we establish (using the Karush-Kuhn-Tucker conditions) a generic form of the optimal solution, the so-called optimality conditions. Second, based on the established optimality conditions, we derive an efficient recursive algorithm, named RNABOX, which solves the allocation problem under study. The RNABOX can be viewed as a generalization of the classical recursive Neyman allocation algorithm, a popular tool for optimum allocation when only upper bounds are imposed on sample strata-sizes. We implement RNABOX in R as a part of our package stratallo which is available from the Comprehensive R Archive Network (CRAN) repository.
Release date: 2024-12-20
6. Bayesian predictive inference of a finite population mean without specifying the relation between the study variable and the covariates
Articles and reports: 12-001-X202400200004
Description: While we avoid specifying the parametric relationship between the study variable and covariates, we illustrate the advantage of including a spatial component to better account for the covariates in our models to make Bayesian predictive inference. We treat each unique covariate combination as an individual stratum, then we use small area estimation techniques to make inference about the finite population mean of the continuous response variable. The two spatial models used are the conditional autoregressive and simple conditional autoregressive models. We include the spatial effects by creating the adjacency matrix via the Mahalanobis distance between covariates. We also show how to incorporate survey weights into the spatial models when dealing with probability survey data. We compare the results of two non-spatial models including the Scott-Smith model and the Battese, Harter, and Fuller model to the spatial models. We illustrate the comparison between the aforementioned models with an application using BMI data from eight counties in California. Our goal is to have neighboring strata yield similar predictions, and to increase the difference between strata that are not neighbors. Ultimately, using the spatial models shows less global pooling compared to the non-spatial models, which was the desired outcome.
Release date: 2024-12-20
7. Robust adaptive survey design for time changes in mixed-mode response propensities
Articles and reports: 12-001-X202400200005
Description: Adaptive survey designs (ASDs) tailor recruitment protocols to population subgroups that are relevant to a survey. In recent years, effective ASD optimization has been the topic of research and several applications. However, the performance of an optimized ASD over time is sensitive to time changes in response propensities. How adaptation strategies can adjust to such variation over time is not yet fully understood. In this paper, we propose a robust optimization approach in the context of sequential mixed-mode surveys employing Bayesian analysis. The approach is formulated as a mathematical programming problem that explicitly accounts for uncertainty due to time change. ASD decisions can then be made by considering time-dependent variation in conditional mode response propensities and between-mode correlations in response propensities. The approach is demonstrated using a case study: the 2014-2017 Dutch Health Survey. We evaluate the sensitivity of ASD performance to 1) the budget level and 2) the length of applicable historic time-series data. We find there is only a moderate dependence on the budget level and the dependence on historic data is moderated by the amount of seasonality during the year.
Release date: 2024-12-20
8. Investigating mode effects in interviewer variances using two representative multi-mode surveys
Articles and reports: 12-001-X202400200006
Description: As mixed-mode designs become increasingly popular, their effects on data quality have attracted much scholarly attention. Most studies focused on the bias properties of mixed-mode designs; few of them have investigated whether mixed-mode designs have heterogeneous variance structures across modes. While many characteristics of mixed-mode designs, such as varied interviewer usage, systematic differences in respondents, varying levels of social desirability bias, among others, may lead to heterogeneous variances in mode-specific point estimates of population means, this study specifically investigates whether interviewer variances remain consistent across different modes in mixed-mode studies. To address this research question, we utilize data collected from two distinct study designs. In the first design, when interviewers are responsible for either face-to-face or telephone mode, we examine whether there are mode differences in interviewer variances for 1) sensitive political questions, 2) international items, 3) and item missing indicators on international items, using the Arab Barometer wave 6 Jordan data. In the second design, we draw on Health and Retirement Study (HRS) 2016 core survey data to examine the question on three topics when interviewers are responsible for both modes. The topics cover 1) the CESD depression scale, 2) interviewer observations, and 3) the physical activity scale. To account for the lack of interpenetrated designs in both data sources, we include respondent-level covariates in our models. We find significant differences in interviewer variances on one item (twelve items in total) in the Arab Barometer study; whereas for HRS, the results are three out of eighteen. Overall, we find the magnitude of the interviewer variances larger in FTF than TEL on sensitive items. We conduct simulations to understand the power to detect mode effects in the typically modest interviewer sample sizes.
Release date: 2024-12-20
9. Models of linkage error for capture-recapture estimation without clerical reviews
Articles and reports: 12-001-X202400200007
Description: The capture-recapture method can be applied to measure the coverage of administrative and big data sources, in official statistics. In its basic form, it involves the linkage of two sources while assuming a perfect linkage and other standard assumptions. In practice, linkage errors arise and are a potential source of bias, where the linkage is based on quasi-identifiers. These errors include false positives and false negatives, where the former arise when linking a pair of records from different units, and the latter arise when not linking a pair of records from the same unit. So far, the existing solutions have resorted to costly clerical reviews, or they have made the restrictive conditional independence assumption. In this work, these requirements are relaxed by modeling the number of links from a record instead. The same approach may be taken to estimate the linkage accuracy without clerical reviews, when linking two sources that each have some undercoverage.
Release date: 2024-12-20
10. Fully synthetic data for complex surveys
Articles and reports: 12-001-X202400200008
Description: When seeking to release public use files for confidential data, statistical agencies can generate fully synthetic data. We propose an approach for making fully synthetic data from surveys collected with complex sampling designs. Our approach adheres to the general strategy proposed by Rubin (1993). Specifically, we generate pseudo-populations by applying the weighted finite population Bayesian bootstrap to account for survey weights, take simple random samples from those pseudo-populations, estimate synthesis models using these simple random samples, and release simulated data drawn from the models as public use files. To facilitate variance estimation, we use the framework of multiple imputation with two data generation strategies. In the first, we generate multiple data sets from each simple random sample. In the second, we generate a single synthetic data set from each simple random sample. We present multiple imputation combining rules for each setting. We illustrate the repeated sampling properties of the combining rules via simulation studies, including comparisons with synthetic data generation based on pseudo-likelihood methods. We apply the proposed methods to a subset of data from the American Community Survey.
Release date: 2024-12-20

Reference (52)

Reference (52) (0 to 10 of 52 results)

1. Departmental Results Report
Notices and consultations: 11-628-X
Description: Departmental Results Reports (DRRs) are part of the Estimates family of documents. Estimates documents support appropriation acts, which specify the amounts and broad purposes for which funds can be spent by the government. The Estimates document family has three parts.

Part I (Government Expenditure Plan) provides an overview of federal spending.

Part II (Main Estimates) lists the financial resources required by individual departments, agencies and Crown corporations for the upcoming fiscal year.

Part III (Departmental Expenditure Plans) consists of two documents. Departmental Plans (DPs) are expenditure plans for each appropriated department and agency (excluding Crown corporations).
Release date: 2024-12-17
2. Ocean and coastal ecosystem extent: Data product specifications
Geographic files and documentation: 16-510-X2024005
Description: This product contains specifications intended for users of the ocean and coastal ecosystem extent geospatial files. This document provides important technical information for users and links to methodology.
Release date: 2024-12-16
3. Ocean and coastal ecosystem extent: Geospatial files
Geographic files and documentation: 16-510-X2024006
Description: This product contains gridded datasets of ocean and coastal ecosystem extent for ocean and coastal areas of Canada. Mapping the extent of ocean ecosystems is the first stage in creating spatially explicit accounts, to help understand the ocean and coastal ecosystems of Canada. The files cover the area from the coastline, defined by the 2021 Statistics Canada Census of Population, to the outer boundary of Canada’s exclusive economic zone (EEZ). Coastal areas of salt marsh are also included in the files.
Release date: 2024-12-16
4. Survey on the Official Language Minority Population: User guide, 2022
Surveys and statistical programs – Documentation: 89-657-X2024009
Description: The Survey on the Official Language Minority Population (SOLMP) user guide contains a description of the survey, along with survey concepts and definitions and an overview of the content development. The target and survey populations, the sample design and sample size are described in the Methodology section. Finally, in the Data Collection module, the collection period and instrument, modes of collection, collection and communications strategies and response rates are provided.
Release date: 2024-12-16
5. Census of Environment: Spatial information products
Geographic files and documentation: 16-510-X
Description: Spatial information products provide users with data for visualization, reference, mapping and spatial analysis using geographical information systems (GIS). Available files include spatial environmental data as well as documentation and metadata. This information is released as part of a suite of products associated with the Census of Environment (CoE). The CoE organizes data about Canada’s natural environment using the System of Environmental-Economic Accounting – Ecosystem Accounting international statistical standard, which takes a spatial approach to accounting for Canada’s ecosystems and natural capital.
Release date: 2024-12-16
6. Persistence and graduation indicators of postsecondary students, 2011/2012 to 2022/2023
Surveys and statistical programs – Documentation: 37-20-00012024003
Description: This technical reference guide is intended for users of the Education and Labour Market Longitudinal Platform (ELMLP). The data for the products associated with this issue are based on the longitudinal Postsecondary Student Information System (PSIS) administrative data files. Statistics Canada has derived a series of annual indicators of public postsecondary students including persistence rates, graduation rates, and average time to graduation by educational qualification, field of study, age group and gender for Canada, the provinces, and the three combined Territories.
Release date: 2024-12-11
7. Technical Reference Guides for the Education and Labour Market Longitudinal Platform (ELMLP)
Surveys and statistical programs – Documentation: 37-20-0001
Description: These reference guides are intended for users of the Education and Labour Market Longitudinal Platform (ELMLP). The guide provides an overview of the Postsecondary Student Information System (PSIS) and the Registered Apprenticeship Information System (RAIS), the general methodology used to create longitudinal indicators, and important technical information for users.
Release date: 2024-12-11
8. Multi-year Consolidated Plan for Research, Modelling and Data Development, 2024 to 2026
Surveys and statistical programs – Documentation: 11-633-X2024005
Description: The Analytical Studies and Modelling Branch is the research (ASMB), modelling, training and access hub of Statistics Canada. It focuses on leveraging the agency’s vast data holdings to generate in-depth insights that support evidence-based policy making and to enable others to do so through analytical training and data access. The ASMB, like other program areas in the agency, works to support Statistics Canada’s overall mission of delivering insights through data for a better Canada.
Release date: 2024-12-06
9. Canadian Export Classification
Classification: 65-209-X
Description: The Canadian Export Classification is a structured, hierarchical classification system based on the Harmonized Description and Coding System. The HS nomenclature is divided into 21 Sections, which in general, group goods produced in the same sector of the economy.
Release date: 2024-12-05
10. Census of Agriculture: Content Consultation Report
Notices and consultations: 95-635-X
Description: To stay relevant, preparing for a new Census of Agriculture requires a thorough evaluation of data requirements. Before each census, Statistics Canada conducts consultations to solicit input and feedback on the Census of Agriculture's content. This report describes those consultations and the process that was followed to test and determine which topics could be potentially retained for the next census.
Release date: 2024-11-27

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