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All (196) (0 to 10 of 196 results)
- 1. Education Indicators in Canada: Report of the Pan-Canadian Education Indicators Program, March 2024Articles and reports: 81-582-X2024001Description: The Pan-Canadian Education Indicators Program (PCEIP) draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. PCEIP products include tables, fact sheets, reports and a methodological handbook. They present indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. The Pan-Canadian Education Indicators Program (PCEIP) is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.Release date: 2024-03-28
- 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: 12-001-X202300200001Description: When a Medicare healthcare provider is suspected of billing abuse, a population of payments X made to that provider over a fixed timeframe is isolated. A certified medical reviewer, in a time-consuming process, can determine the overpayment Y = X - (amount justified by the evidence) associated with each payment. Typically, there are too many payments in the population to examine each with care, so a probability sample is selected. The sample overpayments are then used to calculate a 90% lower confidence bound for the total population overpayment. This bound is the amount demanded for recovery from the provider. Unfortunately, classical methods for calculating this bound sometimes fail to provide the 90% confidence level, especially when using a stratified sample. In this paper, 166 redacted samples from Medicare integrity investigations are displayed and described, along with 156 associated payment populations. The 7,588 examined (Y, X) sample pairs show (1) Medicare audits have high error rates: more than 76% of these payments were considered to have been paid in error; and (2) the patterns in these samples support an “All-or-Nothing” mixture model for (Y, X) previously defined in the literature. Model-based Monte Carlo testing procedures for Medicare sampling plans are discussed, as well as stratification methods based on anticipated model moments. In terms of viability (achieving the 90% confidence level) a new stratification method defined here is competitive with the best of the many existing methods tested and seems less sensitive to choice of operating parameters. In terms of overpayment recovery (equivalent to precision) the new method is also comparable to the best of the many existing methods tested. Unfortunately, no stratification algorithm tested was ever viable for more than about half of the 104 test populations.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200004Description: We present a novel methodology to benchmark county-level estimates of crop area totals to a preset state total subject to inequality constraints and random variances in the Fay-Herriot model. For planted area of the National Agricultural Statistics Service (NASS), an agency of the United States Department of Agriculture (USDA), it is necessary to incorporate the constraint that the estimated totals, derived from survey and other auxiliary data, are no smaller than administrative planted area totals prerecorded by other USDA agencies except NASS. These administrative totals are treated as fixed and known, and this additional coherence requirement adds to the complexity of benchmarking the county-level estimates. A fully Bayesian analysis of the Fay-Herriot model offers an appealing way to incorporate the inequality and benchmarking constraints, and to quantify the resulting uncertainties, but sampling from the posterior densities involves difficult integration, and reasonable approximations must be made. First, we describe a single-shrinkage model, shrinking the means while the variances are assumed known. Second, we extend this model to accommodate double shrinkage, borrowing strength across means and variances. This extended model has two sources of extra variation, but because we are shrinking both means and variances, it is expected that this second model should perform better in terms of goodness of fit (reliability) and possibly precision. The computations are challenging for both models, which are applied to simulated data sets with properties resembling the Illinois corn crop.Release date: 2024-01-03
- Articles and reports: 82-003-X202301200002Description: The validity of survival estimates from cancer registry data depends, in part, on the identification of the deaths of deceased cancer patients. People whose deaths are missed seemingly live on forever and are informally referred to as “immortals”, and their presence in registry data can result in inflated survival estimates. This study assesses the issue of immortals in the Canadian Cancer Registry (CCR) using a recently proposed method that compares the survival of long-term survivors of cancers for which “statistical” cure has been reported with that of similar people from the general population.Release date: 2023-12-20
- Articles and reports: 75-006-X202300100015Description: This study uses data from the Canadian COVID-19 Antibody and Health Survey to describe the current COVID-19 landscape, including infection, reinfection, and acute and long-term symptoms. This study also examines how peoples’ experiences with the virus have evolved in the context of growing immunity, emerging variants, new treatments, and relaxation of public health measures.Release date: 2023-12-08
- Stats in brief: 11-627-M2023059Description: This infographic presents information on pedestrian fatalities collected from the Canadian Coroner and Medical Examiner Database (CCMED). This infographic illustrates demographic profile of the deceased such as sex and age. The product also summarizes information on select circumstances surrounding pedestrian fatalities.Release date: 2023-10-30
- 8. Education Indicators in Canada: Report of the Pan-Canadian Education Indicators Program, October 2023 ArchivedArticles and reports: 81-582-X2023002Description: The Pan-Canadian Education Indicators Program (PCEIP) draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. PCEIP products include tables, fact sheets, reports and a methodological handbook. They present indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. The Pan-Canadian Education Indicators Program (PCEIP) is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.Release date: 2023-10-13
- Articles and reports: 11-621-M2023012Description: Using administrative data, such as goods and services tax (GST) revenue, this study assesses how changing conditions in the economy, such as the end of pandemic-related restrictions, inflationary pressures, strong population growth, tight labour markets and rising interest rates-affected selected service industries in 2022.Release date: 2023-08-15
- 10. Education Indicators in Canada: Report of the Pan-Canadian Education Indicators Program, March 2023 ArchivedArticles and reports: 81-582-X2023001Description: The Pan-Canadian Education Indicators Program (PCEIP) draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. PCEIP products include tables, fact sheets, reports and a methodological handbook. They present indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. The Pan-Canadian Education Indicators Program (PCEIP) is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.Release date: 2023-03-27
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Stats in brief (15)
Stats in brief (15) (0 to 10 of 15 results)
- Stats in brief: 11-627-M2023059Description: This infographic presents information on pedestrian fatalities collected from the Canadian Coroner and Medical Examiner Database (CCMED). This infographic illustrates demographic profile of the deceased such as sex and age. The product also summarizes information on select circumstances surrounding pedestrian fatalities.Release date: 2023-10-30
- Stats in brief: 11-627-M2021025Description:
This infographic highlights a selection of statistics on restaurants, bars and caterers in Canada.
Release date: 2021-03-25 - Stats in brief: 45-28-0001202000100050Description:
This analytical article describes results from the crowdsourced survey "Impacts of COVID-19 on Canadians: Your mental health" with a focus on the mental health of immigrants during the COVID-19 pandemic. More specifically, this article explores the effects of social distancing on mental health, how the pandemic affects the symptoms of anxiety, and how perceived job and financial security affects mental health. This article also discuss the mental health differences between recent immigrants, established immigrants and Canadian born.
Release date: 2020-07-14 - Stats in brief: 82-625-X201800154918Description:
Cycle 4 (2014 and 2015) of the Canadian Health Measures Survey (CHMS), measured the concentrations of the inorganic-related arsenic species (arsenate, arsenite, DMA and MMA) in the urine of approximately 2500 Canadians aged 3 to 79. Results were reported in micrograms of arsenic per litre (µg As/L).
Release date: 2018-02-22 - Stats in brief: 82-625-X201800154919Description:
In 2014 and 2015, the Canadian Health Measures Survey (CHMS) measured the concentrations of parabens (including methyl paraben, ethyl paraben, propyl paraben, and butyl paraben) in the urine of approximately 2500 Canadians aged 3 to 79. Results were reported in micrograms per litre (µg/L).
Release date: 2018-02-22 - 6. Age-specific patterns in the incidence of, and survival from, pancreatic cancer in Canada ArchivedStats in brief: 82-624-X201700114799Description:
This article examines age-specific patterns in the national rates of newly diagnosed cases of pancreatic cancer. Age-specific measures of survival from pancreatic cancer are also examined.
Release date: 2017-04-26 - Stats in brief: 82-624-X201600114667Description:
This article describes the impact on age-standardized cancer incidence and mortality rates of an update to the standard population used to derive them. The impact is assessed by cancer type and by province for 2012, and on trends in cancer rates from 1992 to 2012. Data are from the Canadian Cancer Registry and the Canadian Vital Statistics – Death Database.
Release date: 2016-10-20 - Stats in brief: 88-001-X200900711026Description:
The information in this document is intended primarily to be used by scientific and technological (S&T) policy makers, both federal and provincial, largely as a basis for inter-provincial and inter-sectoral comparisons. The statistics are aggregates of the provincial government and provincial research organization science surveys conducted by Statistics Canada under contract with the provinces, and cover the period 2002/2003 to 2006/2007.
Release date: 2009-11-20 - Stats in brief: 88-001-X200800510678Description:
This service bulletin contains historical and current data on research and development (R&D) expenditures and personnel in Canada, by industry. In Canada, the industrial or business enterprise sector is the largest R&D performer.
Release date: 2008-09-05 - Stats in brief: 88-001-X200800410668Description:
The higher education sector is composed of all universities, colleges of technology and other institutes of postsecondary education, whatever their source of finance or legal status. It also includes all research institutes, experimental stations and clinics operating under the direct control of, or administered by, or associated with higher education establishments.
Release date: 2008-08-14
Articles and reports (178)
Articles and reports (178) (30 to 40 of 178 results)
- Articles and reports: 75-006-X201900100009Description:
This study examines the impact of social capital and ethnocultural characteristics on the evolution of employment income of a cohort of immigrants who arrived in Canada in 2001, based on two linked datasets: the Longitudinal Survey of Immigrants to Canada (LSIC) and the Longitudinal Immigration Database (IMDB). The study examines the employment income of this cohort in their first 15 years in Canada (i.e., from 2002 to 2016).
Release date: 2019-06-19 - Articles and reports: 12-001-X201800254958Description:
Domains (or subpopulations) with small sample sizes are called small areas. Traditional direct estimators for small areas do not provide adequate precision because the area-specific sample sizes are small. On the other hand, demand for reliable small area statistics has greatly increased. Model-based indirect estimators of small area means or totals are currently used to address difficulties with direct estimation. These estimators are based on linking models that borrow information across areas to increase the efficiency. In particular, empirical best (EB) estimators under area level and unit level linear regression models with random small area effects have received a lot of attention in the literature. Model mean squared error (MSE) of EB estimators is often used to measure the variability of the estimators. Linearization-based estimators of model MSE as well as jackknife and bootstrap estimators are widely used. On the other hand, National Statistical Agencies are often interested in estimating the design MSE of EB estimators in line with traditional design MSE estimators associated with direct estimators for large areas with adequate sample sizes. Estimators of design MSE of EB estimators can be obtained for area level models but they tend to be unstable when the area sample size is small. Composite MSE estimators are proposed in this paper and they are obtained by taking a weighted sum of the design MSE estimator and the model MSE estimator. Properties of the MSE estimators under the area level model are studied in terms of design bias, relative root mean squared error and coverage rate of confidence intervals. The case of a unit level model is also examined under simple random sampling within each area. Results of a simulation study show that the proposed composite MSE estimators provide a good compromise in estimating the design MSE.
Release date: 2018-12-20 - Articles and reports: 12-001-X201800254960Description:
Based on auxiliary information, calibration is often used to improve the precision of estimates. However, calibration weighting may not be appropriate for all variables of interest of the survey, particularly those not related to the auxiliary variables used in calibration. In this paper, we propose a criterion to assess, for any variable of interest, the impact of calibration weighting on the precision of the estimated total. This criterion can be used to decide on the weights associated with each survey variable of interest and determine the variables for which calibration weighting is appropriate.
Release date: 2018-12-20 - Articles and reports: 89-28-0001201800100008Description:
This edition presents changes in new home prices for Canada and select census metropolitan areas (CMAs) between August 2017 and August 2018. During this period, Canadians experienced rising mortgage rates, tighter lending rules and some provincial policy interventions.
Release date: 2018-10-31 - 35. Sleep Apnea in Canada, 2016 and 2017 ArchivedArticles and reports: 82-625-X201800154979Description:
This is a health fact sheet about sleep apnea among Canadians 18 to 79 years of age. The results are based on data from cycle 5 (2016-2017) of the Canadian Health Measures Survey.
Release date: 2018-10-24 - Articles and reports: 82-003-X201801000001Description:
Using the 1991 and 2001 Canadian Census Health and Environment Cohorts (CanCHECs), this study examines thyroid cancer incidence over nine years of follow up; presents estimates of the sex-specific relative risk of thyroid cancer according to age, immigrant status, ethnicity, educational attainment and family income; and examines whether these relative risks changed over time.
Release date: 2018-10-17 - Articles and reports: 82-003-X201800900002Description:
This report provides predicted estimates of net survival (NS) for the 2012 to 2014 period. NS estimates for durations of 1, 5 and 10 years are derived for 30 of the most commonly diagnosed cancers in people aged 15 to 99. Five-year age-standardized and age-specific estimates for 2012 to 2014 are compared with corresponding figures for cases diagnosed 20 years previously.
Release date: 2018-09-19 - Articles and reports: 12-001-X201800154963Description:
The probability-sampling-based framework has dominated survey research because it provides precise mathematical tools to assess sampling variability. However increasing costs and declining response rates are expanding the use of non-probability samples, particularly in general population settings, where samples of individuals pulled from web surveys are becoming increasingly cheap and easy to access. But non-probability samples are at risk for selection bias due to differential access, degrees of interest, and other factors. Calibration to known statistical totals in the population provide a means of potentially diminishing the effect of selection bias in non-probability samples. Here we show that model calibration using adaptive LASSO can yield a consistent estimator of a population total as long as a subset of the true predictors is included in the prediction model, thus allowing large numbers of possible covariates to be included without risk of overfitting. We show that the model calibration using adaptive LASSO provides improved estimation with respect to mean square error relative to standard competitors such as generalized regression (GREG) estimators when a large number of covariates are required to determine the true model, with effectively no loss in efficiency over GREG when smaller models will suffice. We also derive closed form variance estimators of population totals, and compare their behavior with bootstrap estimators. We conclude with a real world example using data from the National Health Interview Survey.
Release date: 2018-06-21 - Articles and reports: 16-201-X2018001Description: Forests in Canada tells the story of Canada's forests, providing up-to-date statistics on forest area, forest products and ecosystem services, economic and social contributions of the forest sector and forest management activities and environmental impacts.Release date: 2018-03-14
- 40. Linking the 2006 Census of Population to the Canadian Mortality Database: Descriptive and Validation Study ArchivedArticles and reports: 11-633-X2018014Description:
The Canadian Mortality Database (CMDB) is an administrative database that collects information on cause of death from all provincial and territorial vital statistics registries in Canada. The CMDB lacks subpopulation identifiers to examine mortality rates and disparities among groups such as First Nations, Métis, Inuit and members of visible minority groups. Linkage between the CMDB and the Census of Population is an approach to circumvent this limitation. This report describes a linkage between the CMDB (2006 to 2011) and the 2006 Census of Population, which was carried out using hierarchical deterministic exact matching, with a focus on methodology and validation.
Release date: 2018-02-14
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Journals and periodicals (3)
Journals and periodicals (3) ((3 results))
- 1. Cornerstones of Community: Highlights from the National Survey of Nonprofit and Voluntary Organizations ArchivedJournals and periodicals: 61-533-XDescription:
This publication provides the first national portrait of the many thousands of nonprofit and voluntary organizations found in every Canadian community. The data, from the National Survey of Nonprofit and Voluntary Organizations, reveal a set of organizations that are widely diverse in nature, touching virtually every aspect of Canadians' lives.
Release date: 2005-06-30 - Journals and periodicals: 61-533-SGeography: CanadaDescription:
This booklet summarizes the key results of the first National Survey of Nonprofit and Voluntary Organizations. These organizations have a significant economic presence and serve as vehicles for citizen engagement. However, many report significant challenges to their capacity to fulfill their missions.
Release date: 2005-03-11 - Journals and periodicals: 56-504-XGeography: CanadaDescription:
Networked Canada is the first comprehensive compendium to be published by Statistics Canada on the information and communications technologies (ICT) sector. The compendium has been designed as a profile of the information society, focusing on current trends, as well as an historical overview of the growth and development of the Canadian ICT sector industries. The publication contains two main parts. The first provides a statistical overview of the ICT sector on the basis of key economic variables, including production, employment, international trade, revenue and R&D expenditure. A summary of international ICT sector comparisons for selected variables, using recent data published by the Organization for Economic Cooperation and Development (OECD) is also included here. The ever widening use of, and access to ICTs in the home, at work, in schools and by governments is examined in the second part.
Many different data sources have been used throughout the project, and while all efforts have been made to maximize the amount of data available, it has not been possible in all instances to consistently report for all ICT industries and all relevant variables. The conversion to the new North American Industrial Classification System (NAICS) has largely contributed to these difficulties, and it is expected that a greater range of data will be available once all of the survey programs begin reporting on the basis of this new industry classification.
Release date: 2001-04-27
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