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- Barriers to Care for People with Chronic Health Conditions (1)
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- Freight Rail Services Price Index (1)
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- Value of Inventory Change (1)
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- Experimental New Condominium Apartment Price Index (1)
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- Wastewater-based estimates of drug consumption (1)
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- Canada's external trade classified by Broad Economic Categories (1)
- Survey on Savings for Persons with Disabilities (1)
- COVID-19 epidemiological reports (1)
- Impacts of COVID-19 on Canadian Victim Services (1)
- Survey of Monthly Credit Aggregates (1)
- Impacts of COVID-19 on Health Care Workers: Infection Prevention and Control (ICHCWIPC) (1)
- Survey on Mental Health and Stressful Events (SMHSE) (1)
- Nursing and Residential Care Facility Survey (NRCFS) (1)
- Survey on Before and After School Care in Canada (1)
- COVID-19 Vaccination Coverage Survey (1)
- House of Commons Canada (1)
- Provincial and Territorial Culture Indicators (1)
- Provincial and Territorial Tourism Satellite Account (1)
- Natural Resources Indicators (NRI) (1)
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- ESDC Employee Wellness Survey (1)
- Indigenous Peoples Economic Account (IPEA) (1)
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- Natural Resources Canada (Glaciers) (1)
Results
All (10,026)
All (10,026) (10,000 to 10,010 of 10,026 results)
- 10,001. Test of multiple frame sampling techniques for agricultural surveys: New Brunswick, 1978 ArchivedArticles and reports: 12-001-X197900254835Description: The problem considered in this paper is the estimation of various agricultural variables using a multiple frame approach. The list frame is completely contained within the area frame. The stratification for the list and area frames are based on different criteria. Overall, the multiple frame shows some gains in terms of variance over the area frame. However, a more careful analysis reveals problem areas associated with the list frame such as the method of stratification and the degeneration of list strata over time.Release date: 1979-12-15
- Articles and reports: 12-001-X197900254836Description: This article presents the methodology and analysis of two major pretests undertaken in order to compare the effectiveness of different interviewing methods and to assess the feasibility of collecting information which would meet Victimization Survey information requirements.Release date: 1979-12-15
- 10,003. A personal view of hot deck imputation procedures ArchivedArticles and reports: 12-001-X197900254832Description:
A Hot Deck imputation procedure is defined to be one where an incomplete response is completed by using values from one or more other records on the same file and the choice of these records varies with the record requiring imputation.
General approaches to Hot Deck imputation are outlined, with emphasis on the interaction between the edit constraints and the imputation procedures. Distance functions can be constructed on a mixture of categorical and numeric fields, can be modified to take account of the relative importance of fields and can discriminate against less desirable donors. Matching fields may be correlated with missing fields, may be linked with missing fields by edits or may be natural stratification variables; but increasing the number of matching fields does not necessarily result in a better match. It is important to audit the imputation process and to summarize its performance.
Hot Deck procedures should be evaluated to study the bias and reliability of the estimates, donor usage and frequency of imputation failure in terms of a variety of conditions of the data and variations of the imputation procedure. It appears that the only generally available approach to evaluation is by simulation.
Release date: 1979-12-14 - 10,004. Data, statistics, information - Some issues of the Canadian Social Statistics Scene ArchivedArticles and reports: 12-001-X197900254833Description:
This paper looks at the current state of development of social statistics in Canada. Some key concepts related to statistics and social information are defined and discussed. The availability and analysis of administrative data is highlighted, along with the need for social surveys. Suggestions are made about the types of data analysis needed for the development of social decision models to meet policy requirements. Finally, an outline of priorities for future work toward the effective use of social statistics is given.
Release date: 1979-12-14 - 10,005. Management of information: Future trends ArchivedArticles and reports: 12-001-X197900100001Description: This paper discusses the management of information within the context of the information industry and indicates some likely future trends related thereto. The information industry itself is first briefly described. Then the process used in producing information, the organizational structure required for such production, and the legislation relating to the information industry are discussed in turn. Finally, some approaches to solving the problems of the future are suggested.Release date: 1979-06-15
- 10,006. Non-response in the Canadian Labour Force Survey ArchivedArticles and reports: 12-001-X197900100002Description: This paper includes a description of interviewer techniques and procedures used to minimize non-response, an outline of methods used to monitor and control non-response, and a discussion of how non-respondents are treated in the data processing and estimation stages of the Canadian Labour Force Survey. Recent non-response rates as well as data on the characteristics of non-respondents are also given. It is concluded that a yearly non-response rate of approximately 5 percent is probably the best that can be achieved in the Labour Force Survey.Release date: 1979-06-15
- 10,007. An empirical investigation of an improved method of measuring correlated response variance ArchivedArticles and reports: 12-001-X197900100003Description: Two methods for estimating the correlated response variance of a survey estimator are studied by way of both theoretical comparison and empirical investigation. The variance of these estimators is discussed and the effects of outliers examined. Finally, an improved estimator is developed and evaluated.Release date: 1979-06-15
- 10,008. Selecting a sample of size n with PPSWOR from a finite population ArchivedArticles and reports: 12-001-X197900100004Description: Let U = {1, 2, …, i, …, N} be a finite population of N identifiable units. A known “size measure” x_i is associated with unit i; i = 1, 2, ..., N. A sampling procedure for selecting a sample of size n (2 < n < N) with probability proportional to size (PPS) and without replacement (WOR) from the population is proposed. With this method, the inclusion probability is proportional to size (IPPS) for each unit in the population.Release date: 1979-06-15
- 10,009. On the inclusion of large units in simple random sampling ArchivedArticles and reports: 12-001-X197900100005Description: Approximate cutoff rules for stratifying a population into a take-all and take-some universe have been given by Dalenius (1950) and Glasser (1962). They expressed the cutoff value (that value which delineates the boundary of the take-all and take-some) as a function of the mean, the sampling weight and the population variance. Their cutoff values were derived on the assumption that a single random sample of size n was to be drawn without replacement from the population of size N.In the present context, exact and approximate cutoff rules have been worked out for a similar situation. Rather than providing the sample size of the sample, the precision (coefficient of variation) is given. Note that in many sampling situations, the sampler is given a set of objectives in terms of reliability and not sample size. The result is particularly useful for determining the take-all - take-some boundary for samples drawn from a known population. The procedure is also extended to ratio estimation.Release date: 1979-06-15
- 10,010. Unbiased estimation of proportions under sequential sampling ArchivedArticles and reports: 12-001-X197900100006Description: Under a sequential sampling plan, the proportion defective in the sample is generally a biased estimator of the population value. In this paper, an unbiased estimator is given. Also, an unbiased estimator of its variance is derived. These results are applied to an estimation problem from the 1976 Canadian Census.Release date: 1979-06-15
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Stats in brief (2,683)
Stats in brief (2,683) (20 to 30 of 2,683 results)
- Stats in brief: 11-627-M2024032Description: This infographic is a visual representation of short-term rental (STR) activity across Canada, focusing particularly on the subset of STRs that could potentially be used for long-term housing. This subset of STRs is referred to as potential long-term dwellings (PLTDs), it comprises entire units listed for more than 180 days a year, excluding vacation-type properties.Release date: 2024-07-30
- Stats in brief: 11-001-X202421218843Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-07-30
- Stats in brief: 11-627-M2024030Description: Key statistics about crime in Canada are presented in this infographic. Findings on changes to the Crime Severity Index (CSI) at the national and provincial, territorial levels are presented. Also included are the categories of crime which were reported in 2023.Release date: 2024-07-25
- Stats in brief: 11-001-X20242073555Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-07-25
- Stats in brief: 11-001-X20242074751Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-07-25
- Stats in brief: 11-631-X2024005Description: This presentation explores linkages between innovation, technology adoption and productivity. It highlights recent estimates of labour and multifactor productivity growth, drawing on recent surveys that can be used to profile the innovation and technological stance of Canadian businesses. It is intended to support ongoing research on the competitiveness of Canada’s economy.Release date: 2024-07-24
- Stats in brief: 11-001-X202420622588Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-07-24
- Stats in brief: 11-001-X202420624744Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-07-24
- Stats in brief: 11-001-X20242053308Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-07-23
- Stats in brief: 11-001-X20242013556Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-07-19
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Articles and reports (7,021)
Articles and reports (7,021) (30 to 40 of 7,021 results)
- Articles and reports: 12-001-X202400100004Description: Non-probability samples are being increasingly explored in National Statistical Offices as an alternative to probability samples. However, it is well known that the use of a non-probability sample alone may produce estimates with significant bias due to the unknown nature of the underlying selection mechanism. Bias reduction can be achieved by integrating data from the non-probability sample with data from a probability sample provided that both samples contain auxiliary variables in common. We focus on inverse probability weighting methods, which involve modelling the probability of participation in the non-probability sample. First, we consider the logistic model along with pseudo maximum likelihood estimation. We propose a variable selection procedure based on a modified Akaike Information Criterion (AIC) that properly accounts for the data structure and the probability sampling design. We also propose a simple rank-based method of forming homogeneous post-strata. Then, we extend the Classification and Regression Trees (CART) algorithm to this data integration scenario, while again properly accounting for the probability sampling design. A bootstrap variance estimator is proposed that reflects two sources of variability: the probability sampling design and the participation model. Our methods are illustrated using Statistics Canada’s crowdsourcing and survey data.Release date: 2024-06-25
- Articles and reports: 12-001-X202400100005Description: In this rejoinder, I address the comments from the discussants, Dr. Takumi Saegusa, Dr. Jae-Kwang Kim and Ms. Yonghyun Kwon. Dr. Saegusa’s comments about the differences between the conditional exchangeability (CE) assumption for causal inferences versus the CE assumption for finite population inferences using nonprobability samples, and the distinction between design-based versus model-based approaches for finite population inference using nonprobability samples, are elaborated and clarified in the context of my paper. Subsequently, I respond to Dr. Kim and Ms. Kwon’s comprehensive framework for categorizing existing approaches for estimating propensity scores (PS) into conditional and unconditional approaches. I expand their simulation studies to vary the sampling weights, allow for misspecified PS models, and include an additional estimator, i.e., scaled adjusted logistic propensity estimator (Wang, Valliant and Li (2021), denoted by sWBS). In my simulations, it is observed that the sWBS estimator consistently outperforms or is comparable to the other estimators under the misspecified PS model. The sWBS, as well as WBS or ABS described in my paper, do not assume that the overlapped units in both the nonprobability and probability reference samples are negligible, nor do they require the identification of overlap units as needed by the estimators proposed by Dr. Kim and Ms. Kwon.Release date: 2024-06-25
- Articles and reports: 12-001-X202400100006Description: In some of non-probability sample literature, the conditional exchangeability assumption is considered to be necessary for valid statistical inference. This assumption is rooted in causal inference though its potential outcome framework differs greatly from that of non-probability samples. We describe similarities and differences of two frameworks and discuss issues to consider when adopting the conditional exchangeability assumption in non-probability sample setups. We also discuss the role of finite population inference in different approaches of propensity scores and outcome regression modeling to non-probability samples.Release date: 2024-06-25
- Articles and reports: 12-001-X202400100007Description: Pseudo weight construction for data integration can be understood in the two-phase sampling framework. Using the two-phase sampling framework, we discuss two approaches to the estimation of propensity scores and develop a new way to construct the propensity score function for data integration using the conditional maximum likelihood method. Results from a limited simulation study are also presented.Release date: 2024-06-25
- Articles and reports: 12-001-X202400100008Description: Nonprobability samples emerge rapidly to address time-sensitive priority topics in different areas. These data are timely but subject to selection bias. To reduce selection bias, there has been wide literature in survey research investigating the use of propensity-score (PS) adjustment methods to improve the population representativeness of nonprobability samples, using probability-based survey samples as external references. Conditional exchangeability (CE) assumption is one of the key assumptions required by PS-based adjustment methods. In this paper, I first explore the validity of the CE assumption conditional on various balancing score estimates that are used in existing PS-based adjustment methods. An adaptive balancing score is proposed for unbiased estimation of population means. The population mean estimators under the three CE assumptions are evaluated via Monte Carlo simulation studies and illustrated using the NIH SARS-CoV-2 seroprevalence study to estimate the proportion of U.S. adults with COVID-19 antibodies from April 01-August 04, 2020.Release date: 2024-06-25
- Articles and reports: 12-001-X202400100009Description: Our comments respond to discussion from Sen, Brick, and Elliott. We weigh the potential upside and downside of Sen’s suggestion of using machine learning to identify bogus respondents through interactions and improbable combinations of variables. We join Brick in reflecting on bogus respondents’ impact on the state of commercial nonprobability surveys. Finally, we consider Elliott’s discussion of solutions to the challenge raised in our study.Release date: 2024-06-25
- Articles and reports: 12-001-X202400100010Description: This discussion summarizes the interesting new findings around measurement errors in opt-in surveys by Kennedy, Mercer and Lau (KML). While KML enlighten readers about “bogus responding” and possible patterns in them, this discussion suggests combining these new-found results with other avenues of research in nonprobability sampling, such as improvement of representativeness.Release date: 2024-06-25
- Articles and reports: 12-001-X202400100011Description: Kennedy, Mercer, and Lau explore misreporting by respondents in non-probability samples and discover a new feature, namely that of deliberate misreporting of demographic characteristics. This finding suggests that the “arms race” between researchers and those determined to disrupt the practice of social science is not over and researchers need to account for such respondents if using high-quality probability surveys to help reduce error in non-probability samples.Release date: 2024-06-25
- Articles and reports: 12-001-X202400100012Description: Nonprobability samples are quick and low-cost and have become popular for some types of survey research. Kennedy, Mercer and Lau examine data quality issues associated with opt-in nonprobability samples frequently used in the United States. They show that the estimates from these samples have serious problems that go beyond representativeness. A total survey error perspective is important for evaluating all types of surveys.Release date: 2024-06-25
- Articles and reports: 12-001-X202400100013Description: Statistical approaches developed for nonprobability samples generally focus on nonrandom selection as the primary reason survey respondents might differ systematically from the target population. Well-established theory states that in these instances, by conditioning on the necessary auxiliary variables, selection can be rendered ignorable and survey estimates will be free of bias. But this logic rests on the assumption that measurement error is nonexistent or small. In this study we test this assumption in two ways. First, we use a large benchmarking study to identify subgroups for which errors in commercial, online nonprobability samples are especially large in ways that are unlikely due to selection effects. Then we present a follow-up study examining one cause of the large errors: bogus responding (i.e., survey answers that are fraudulent, mischievous or otherwise insincere). We find that bogus responding, particularly among respondents identifying as young or Hispanic, is a significant and widespread problem in commercial, online nonprobability samples, at least in the United States. This research highlights the need for statisticians working with commercial nonprobability samples to address bogus responding and issues of representativeness – not just the latter.Release date: 2024-06-25
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Journals and periodicals (322)
Journals and periodicals (322) (40 to 50 of 322 results)
- Journals and periodicals: 91F0015MGeography: CanadaDescription: Demographic documentsis a series of texts intended for scholars and researchers, published occasionally by the Demography Division of Statistics Canada for their methodological, analytical or descriptive interest in the population field.Release date: 2024-02-02
- Journals and periodicals: 11-633-XDescription: Papers in this series provide background discussions of the methods used to develop data for economic, health, and social analytical studies at Statistics Canada. They are intended to provide readers with information on the statistical methods, standards and definitions used to develop databases for research purposes. All papers in this series have undergone peer and institutional review to ensure that they conform to Statistics Canada's mandate and adhere to generally accepted standards of good professional practice.Release date: 2024-01-22
- Journals and periodicals: 85-603-XDescription: This article presents results from the first Survey of Sexual Misconduct in the Canadian Armed Forces. Namely, the prevalence of general sexualized behaviour in the workplace; discrimination on the basis of sex, sexual orientation, or gender identity; personal experiences of discrimination or sexualized behaviour; the prevalence of sexual assault; and knowledge of policies on sexual misconduct and perceptions of responses to sexual misconduct are examined. Where possible, results are analyzed by sex, environmental command, type of service, age, rank, and number of years of service.Release date: 2023-12-05
- Journals and periodicals: 85-005-XGeography: CanadaDescription: This publication features short, informative articles focusing on specific justice-related issues. For more in-depth articles on justice in Canada, see also Juristat, Catalogue no. 85-002-X.Release date: 2023-12-04
- Journals and periodicals: 21-004-XGeography: CanadaDescription:
Each issue contains a short article highlighting statistical insights on themes relating to agriculture, food and rural issues.
Release date: 2023-11-30 - Table: 57-003-XDescription: This publication presents energy balance sheets in natural units and heat equivalents in primary and secondary forms, by province. Each balance sheet shows data on production, trade, interprovincial movements, conversion and consumption by sector. Analytical tables and details on non-energy products are also included. It includes explanatory notes, a historical energy summary table and data analysis. The publication also presents data on natural gas liquids, electricity generated from fossil fuels, solid wood waste and spent pulping liquor.Release date: 2023-11-20
- Journals and periodicals: 45-26-0001Description: 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: 2023-11-14
- Journals and periodicals: 62F0026MDescription: This series provides detailed documentation on the issues, concepts, methodology, data quality and other relevant research related to household expenditures from the Survey of Household Spending, the Homeowner Repair and Renovation Survey and the Food Expenditure Survey.Release date: 2023-10-18
- Journals and periodicals: 12-206-XDescription: This report summarizes the annual achievements of the Methodology Research and Development Program (MRDP) sponsored by the Modern Statistical Methods and Data Science Branch at Statistics Canada. This program covers research and development activities in statistical methods with potentially broad application in the agency’s statistical programs; these activities would otherwise be less likely to be carried out during the provision of regular methodology services to those programs. The MRDP also includes activities that provide support in the application of past successful developments in order to promote the use of the results of research and development work. Selected prospective research activities are also presented.Release date: 2023-10-11
- Journals and periodicals: 16-001-MDescription: The series covers environment accounts and indicators, environmental surveys, spatial environmental information and other research related to environmental statistics. The technical paper series is intended to stimulate discussion on a range of environmental topics.Release date: 2023-09-13
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