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All (1,889) (1,770 to 1,780 of 1,889 results)

  • Articles and reports: 12-001-X198600214451
    Description:

    The Canadian Census of Construction (COC) uses a complex plan for sampling small businesses (those having a gross income of less than $750,000). Stratified samples are drawn from overlapping frames. Two subsamples are selected independently from one of the samples, and more detailed information is collected on the businesses in the subsamples. There are two possible methods of estimating totals for the variables collected in the subsamples. The first approach is to determine weights based on sampling rates. A number of different weights must be used. The second approach is to impute values to the businesses included in the sample but not in the subsamples. This approach creates a complete “rectangular” sample file, and a single weight may then be used to produce estimates for the population. This “large-scale imputation” technique is presently applied for the Census of Construction. The purpose of the study is to compare the figures obtained using various estimation techniques with the estimates produced by means of large-scale imputation.

    Release date: 1986-12-15

  • Articles and reports: 12-001-X198600214462
    Description:

    In the presence of unit nonresponse, two types of variables can sometimes be observed for units in the “intended” sample s, namely, (a) variables used to estimate the response mechanism (the response probabilities), (b) variables (here called co-variates) that explain the variable of interest, in the usual regression theory sense. This paper, based on Särndal and Swensson (1985 a, b), discusses nonresponse adjusted estimators with and without explicit involvement of co-variates. We conclude that the presence of strong co-variates in an estimator induces several favourable properties. Among other things, estimators making use of co-variates are considerably more resistant to nonresponse bias. We discuss the calculation of standard error and valid confidence intervals for estimators involving co-variates. The structure of the standard error is examined and discussed.

    Release date: 1986-12-15

  • Articles and reports: 12-001-X198600214463
    Description:

    The procedure of subsampling the nonrespondents suggested by Hansen and Hurwitz (1946) is considered. Post-stratification prior to the subsampling is examined. For the mean of a characteristic of interest, ratio estimators suitable for different practical situations are proposed and their merits are examined. Suitable ratio estimators are also suggested for the situations in which the Hard-Core are present.

    Release date: 1986-12-15

  • Articles and reports: 12-001-X198600114404
    Description:

    Missing survey data occur because of total nonresponse and item nonresponse. The standard way to attempt to compensate for total nonresponse is by some form of weighting adjustment, whereas item nonresponses are handled by some form of imputation. This paper reviews methods of weighting adjustment and imputation and discusses their properties.

    Release date: 1986-06-16

  • Articles and reports: 12-001-X198600114437
    Description:

    In this paper, different types of response/nonresponse and associated measures such as rates are provided and discussed together with their implications on both estimation and administrative procedures. The missing data problems lead to inconsistent terminology related to nonresponse such as completion rates, eligibility rates, contact rates, and refusal rates, many of which can be defined in different ways. In addition, there are item nonresponse rates as well as characteristic response rates. Depending on the uses, the rates may be weighted or unweighted.

    Release date: 1986-06-16

  • Articles and reports: 12-001-X198600114438
    Description:

    Using the optimal estimating functions for survey sampling estimation (Godambe and Thompson 1986), we obtain some optimality results for nonresponse situations in survey sampling.

    Release date: 1986-06-16

  • Articles and reports: 12-001-X198600114439
    Description:

    Multiple imputation is a technique for handling survey nonresponse that replaces each missing value created by nonresponse by a vector of possible values that reflect uncertainty about which values to impute. A simple example and brief overview of the underlying theory are used to introduce the general procedure.

    Release date: 1986-06-16

  • Articles and reports: 12-001-X198600114440
    Description:

    Statistics Canada has undertaken a project to develop a generalized edit and imputation system, the intent of which is to meet the processing requirements of most of its surveys. The various approaches to imputation for item non-response, which have been proposed, will be discussed. Important issues related to the implementation of these proposals into a generalized setting will also be addressed.

    Release date: 1986-06-16

  • Articles and reports: 12-001-X198600114441
    Description:

    The analysis of survey data becomes difficult in the presence of incomplete responses. By the use of the maximum likelihood method, estimators for the parameters of interest and test statistics can be generated. In this paper the maximum likelihood estimators are given for the case where the data is considered missing at random. A method for imputing the missing values is considered along with the problem of estimating the change points in the mean. Possible extensions of the results to structured covariances and to non-randomly incomplete data are also proposed.

    Release date: 1986-06-16

  • Articles and reports: 12-001-X198600114442
    Description:

    For periodic business surveys which are conducted on a monthly, quarterly or annual basis, the data for responding units must be edited and the data for non-responding units must be imputed. This paper reports on methods which can be used for editing and imputing data. The editing is comprised of consistency and statistical edits. The imputation is done for both total non-response and partial non-response.

    Release date: 1986-06-16
Stats in brief (81)

Stats in brief (81) (0 to 10 of 81 results)

  • Stats in brief: 11-001-X202411338008
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-04-22

  • Stats in brief: 11-637-X
    Description: This product presents data on the Sustainable Development Goals. They present an overview of the 17 Goals through infographics by leveraging data currently available to report on Canada’s progress towards the 2030 Agenda for Sustainable Development.
    Release date: 2024-01-25

  • Stats in brief: 11-001-X202402237898
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-01-22

  • Stats in brief: 89-20-00062023001
    Description: This course is intended for Government of Canada employees who would like to learn about evaluating the quality of data for a particular use. Whether you are a new employee interested in learning the basics, or an experienced subject matter expert looking to refresh your skills, this course is here to help.
    Release date: 2023-07-17

  • Stats in brief: 98-20-00032021011
    Description: This video explains the key concepts of different levels of aggregation of income data such as household and family income; income concepts derived from key income variables such as adjusted income and equivalence scale; and statistics used for income data such as median and average income, quartiles, quintiles, deciles and percentiles.
    Release date: 2023-03-29

  • Stats in brief: 98-20-00032021012
    Description: This video builds on concepts introduced in the other videos on income. It explains key low-income concepts - Market Basket Measure (MBM), Low income measure (LIM) and Low-income cut-offs (LICO) and the indicators associated with these concepts such as the low-income gap and the low-income ratio. These concepts are used in analysis of the economic well-being of the population.
    Release date: 2023-03-29

  • Stats in brief: 11-001-X202231822683
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2022-11-14

  • 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

  • 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

  • Stats in brief: 89-20-00062022001
    Description:

    Gathering, exploring, analyzing and interpreting data are essential steps in producing information that benefits society, the economy and the environment. To properly conduct these processes, data ethics ethics must be upheld in order to ensure the appropriate use of data.

    Release date: 2022-05-24
Articles and reports (1,783)

Articles and reports (1,783) (60 to 70 of 1,783 results)

  • Articles and reports: 45-20-00022023004
    Description: Gender-based Analysis Plus (GBA Plus) is an analytical tool developed by Women and Gender Equality Canada (WAGE) to support the development of responsive and inclusive initiatives, including policies, programs, and other initiatives. This information sheet presents the usefulness of GBA Plus for disaggregating and analyzing data to identify the groups most affected by certain issues, such as overqualification.
    Release date: 2023-11-27

  • Articles and reports: 75F0002M2023005
    Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and systems used to produce income estimates with the release of its 2021 reference year estimates. This paper describes the changes and presents the approximate net result of these changes on income estimates using data for 2019 and 2020. The changes described in this paper highlight the ways in which data quality has been improved while producing minimal impact on key CIS estimates and trends.
    Release date: 2023-08-29

  • Articles and reports: 12-001-X202300100001
    Description: Recent work in survey domain estimation allows for estimation of population domain means under a priori assumptions expressed in terms of linear inequality constraints. For example, it might be known that the population means are non-decreasing along ordered domains. Imposing the constraints has been shown to provide estimators with smaller variance and tighter confidence intervals. In this paper we consider a formal test of the null hypothesis that all the constraints are binding, versus the alternative that at least one constraint is non-binding. The test of constant versus increasing domain means is a special case. The power of the test is substantially better than the test with the same null hypothesis and an unconstrained alternative. The new test is used with data from the National Survey of College Graduates, to show that salaries are positively related to the subject’s father’s educational level, across fields of study and over several years of cohorts.
    Release date: 2023-06-30

  • Articles and reports: 12-001-X202300100002
    Description: We consider regression analysis in the context of data integration. To combine partial information from external sources, we employ the idea of model calibration which introduces a “working” reduced model based on the observed covariates. The working reduced model is not necessarily correctly specified but can be a useful device to incorporate the partial information from the external data. The actual implementation is based on a novel application of the information projection and model calibration weighting. The proposed method is particularly attractive for combining information from several sources with different missing patterns. The proposed method is applied to a real data example combining survey data from Korean National Health and Nutrition Examination Survey and big data from National Health Insurance Sharing Service in Korea.
    Release date: 2023-06-30

  • Articles and reports: 12-001-X202300100003
    Description: To improve the precision of inferences and reduce costs there is considerable interest in combining data from several sources such as sample surveys and administrative data. Appropriate methodology is required to ensure satisfactory inferences since the target populations and methods for acquiring data may be quite different. To provide improved inferences we use methodology that has a more general structure than the ones in current practice. We start with the case where the analyst has only summary statistics from each of the sources. In our primary method, uncertain pooling, it is assumed that the analyst can regard one source, survey r, as the single best choice for inference. This method starts with the data from survey r and adds data from those other sources that are shown to form clusters that include survey r. We also consider Dirichlet process mixtures, one of the most popular nonparametric Bayesian methods. We use analytical expressions and the results from numerical studies to show properties of the methodology.
    Release date: 2023-06-30

  • Articles and reports: 12-001-X202300100004
    Description: The Dutch Health Survey (DHS), conducted by Statistics Netherlands, is designed to produce reliable direct estimates at an annual frequency. Data collection is based on a combination of web interviewing and face-to-face interviewing. Due to lockdown measures during the Covid-19 pandemic there was no or less face-to-face interviewing possible, which resulted in a sudden change in measurement and selection effects in the survey outcomes. Furthermore, the production of annual data about the effect of Covid-19 on health-related themes with a delay of about one year compromises the relevance of the survey. The sample size of the DHS does not allow the production of figures for shorter reference periods. Both issues are solved by developing a bivariate structural time series model (STM) to estimate quarterly figures for eight key health indicators. This model combines two series of direct estimates, a series based on complete response and a series based on web response only and provides model-based predictions for the indicators that are corrected for the loss of face-to-face interviews during the lockdown periods. The model is also used as a form of small area estimation and borrows sample information observed in previous reference periods. In this way timely and relevant statistics describing the effects of the corona crisis on the development of Dutch health are published. In this paper the method based on the bivariate STM is compared with two alternative methods. The first one uses a univariate STM where no correction for the lack of face-to-face observation is applied to the estimates. The second one uses a univariate STM that also contains an intervention variable that models the effect of the loss of face-to-face response during the lockdown.
    Release date: 2023-06-30

  • Articles and reports: 12-001-X202300100005
    Description: Weight smoothing is a useful technique in improving the efficiency of design-based estimators at the risk of bias due to model misspecification. As an extension of the work of Kim and Skinner (2013), we propose using weight smoothing to construct the conditional likelihood for efficient analytic inference under informative sampling. The Beta prime distribution can be used to build a parameter model for weights in the sample. A score test is developed to test for model misspecification in the weight model. A pretest estimator using the score test can be developed naturally. The pretest estimator is nearly unbiased and can be more efficient than the design-based estimator when the weight model is correctly specified, or the original weights are highly variable. A limited simulation study is presented to investigate the performance of the proposed methods.
    Release date: 2023-06-30

  • Articles and reports: 12-001-X202300100006
    Description: My comments consist of three components: (1) A brief account of my professional association with Chris Skinner. (2) Observations on Skinner’s contributions to statistical disclosure control, (3) Some comments on making inferences from masked survey data.
    Release date: 2023-06-30

  • Articles and reports: 12-001-X202300100007
    Description: I provide an overview of the evolution of Statistical Disclosure Control (SDC) research over the last decades and how it has evolved to handle the data revolution with more formal definitions of privacy. I emphasize the many contributions by Chris Skinner in the research areas of SDC. I review his seminal research, starting in the 1990’s with his work on the release of UK Census sample microdata. This led to a wide-range of research on measuring the risk of re-identification in survey microdata through probabilistic models. I also focus on other aspects of Chris’ research in SDC. Chris was the recipient of the 2019 Waksberg Award and sadly never got a chance to present his Waksberg Lecture at the Statistics Canada International Methodology Symposium. This paper follows the outline that Chris had prepared in preparation for that lecture.
    Release date: 2023-06-30

  • Articles and reports: 12-001-X202300100008
    Description: This brief tribute reviews Chris Skinner’s main scientific contributions.
    Release date: 2023-06-30
Journals and periodicals (25)

Journals and periodicals (25) (10 to 20 of 25 results)

  • Journals and periodicals: 88F0006X
    Geography: Canada
    Description:

    Statistics Canada is engaged in the "Information System for Science and Technology Project" to develop useful indicators of activity and a framework to tie them together into a coherent picture of science and technology (S&T) in Canada. The working papers series is used to publish results of the different initiatives conducted within this project. The data are related to the activities, linkages and outcomes of S&T. Several key areas are covered such as: innovation, technology diffusion, human resources in S&T and interrelations between different actors involved in S&T. This series also presents data tabulations taken from regular surveys on research and development (R&D) and S&T and made possible by the project.

    Release date: 2011-12-23

  • Journals and periodicals: 12-587-X
    Description:

    This publication shows readers how to design and conduct a census or sample survey. It explains basic survey concepts and provides information on how to create efficient and high quality surveys. It is aimed at those involved in planning, conducting or managing a survey and at students of survey design courses.

    This book contains the following information:

    -how to plan and manage a survey;-how to formulate the survey objectives and design a questionnaire; -things to consider when determining a sample design (choosing between a sample or a census, defining the survey population, choosing a survey frame, identifying possible sources of survey error); -choosing a method of collection (self-enumeration, personal interviews or telephone interviews; computer-assisted versus paper-based questionnaires); -organizing and conducting data collection operations;-determining the sample size, allocating the sample across strata and selecting the sample; -methods of point estimation and variance estimation, and data analysis; -the use of administrative data, particularly during the design and estimation phases-how to process the data (which consists of all data handling activities between collection and estimation) and use quality control and quality assurance measures to minimize and control errors during various survey steps; and-disclosure control and data dissemination.

    This publication also includes a case study that illustrates the steps in developing a household survey, using the methods and principles presented in the book. This publication was previously only available in print format and originally published in 2003.

    Release date: 2010-09-27

  • Journals and periodicals: 89-639-X
    Geography: Canada
    Description:

    Beginning in late 2006, the Social and Aboriginal Statistics Division of Statistics Canada embarked on the process of review of questions used in the Census and in surveys to produce data about Aboriginal peoples (North American Indian, Métis and Inuit). This process is essential to ensure that Aboriginal identification questions are valid measures of contemporary Aboriginal identification, in all its complexity. Questions reviewed included the following (from the Census 2B questionnaire):- the Ethnic origin / Aboriginal ancestry question;- the Aboriginal identity question;- the Treaty / Registered Indian question; and- the Indian band / First Nation Membership question.

    Additional testing was conducted on Census questions with potential Aboriginal response options: the population group question (also known as visible minorities), and the Religion question. The review process to date has involved two major steps: regional discussions with data users and stakeholders, and qualitative testing. The regional discussions with over 350 users of Aboriginal data across Canada were held in early 2007 to examine the four questions used on the Census and other surveys of Statistics Canada. Data users included National Aboriginal organizations, Aboriginal Provincial and Territorial Organizations, Federal, Provincial and local governments, researchers and Aboriginal service organizations. User feedback showed that main areas of concern were data quality, undercoverage, the wording of questions, and the importance of comparability over time.

    Release date: 2009-04-17

  • Journals and periodicals: 16-254-X
    Geography: Canada
    Description:

    This report presents details on the data sources and methods underlying the air quality indicators as they were reported in Canadian Environmental Sustainability Indicators, 2007 (16-251-XWE). The air quality indicators focus on human exposure to ground-level ozone and fine particulate matter.

    Details on the indicators reported after 2007 can be found on Environment Canada's site: &&www.ec.gc.ca/indicateurs-indicators/

    Release date: 2008-06-20

  • Journals and periodicals: 16-256-X
    Geography: Canada
    Description:

    This report presents details on the data sources and methods underlying the freshwater quality indicator as it was reported in the Canadian Environmental Sustainability Indicators, 2007 (16-251-XWE). The national freshwater quality indicator provides an overall measure of the suitability of water bodies to support aquatic life in selected monitoring sites in Canada.

    Details on this indicator reported after 2007 can be found on Environment Canada's site: www.ec.gc.ca/indicateurs-indicators/

    Release date: 2008-06-20

  • Journals and periodicals: 89-629-X
    Geography: Canada
    Description:

    This report summarizes the main issues raised in these meetings. Four questions used to identify Aboriginal people from the Census and surveys were considered in the discussions.Statistics Canada regularly reviews the questions used on the Census and other surveys to ensure that the resulting data are representative of the population. As a first step in the process to review the questions used to produce data about First Nations, Inuit and Métis populations, regional discussions were held with more than 350 users of Aboriginal data in over 40 locations across Canada during the winter, spring and early summer of 2007.

    This report summarizes the main issues raised in these meetings. Four questions used to identify Aboriginal people from the Census and surveys were considered in the discussions.

    Release date: 2008-05-27

  • Journals and periodicals: 85-569-X
    Geography: Canada
    Description:

    This feasibility report provides a blueprint for improving data on fraud in Canada through a survey of businesses and through amendments to the Uniform Crime Reporting (UCR) Survey. Presently, national information on fraud is based on official crime statistics reported by police services to the Uniform Crime Reporting Survey. These data, however, do not reflect the true nature and extent of fraud in Canada due to under-reporting of fraud by individuals and businesses, and due to inconsistencies in the way frauds are counted within the UCR Survey. This feasibility report concludes that a better measurement of fraud in Canada could be obtained through a survey of businesses. The report presents the information priorities of government departments, law enforcement and the private sector with respect to the issue of fraud and makes recommendations on how a survey of businesses could help fulfill these information needs.

    To respond to information priorities, the study recommends surveying the following types of business establishments: banks, payment companies (i.e. credit card and debit card companies), selected retailers, property and casualty insurance carriers, health and disability insurance carriers and selected manufacturers. The report makes recommendations regarding survey methodology and questionnaire content, and provides estimates for timeframes and cost.

    The report also recommends changes to the UCR Survey in order to improve the way in which incidents are counted and to render the data collected more relevant with respect to the information priorities raised by government, law enforcement and the private sector during the feasibility study.

    Release date: 2006-04-11

  • Journals and periodicals: 92-134-X
    Description:

    This document summarizes the results of content analyses of the 2004 Census Test. The first section briefly explains the context of the content analyses by describing the nature of the sample, its limitations and the strategies used to evaluate data quality. The second section provides an overview of the results for questions that have not changed since the 2001 Census by describing the similarities between 2001 and 2004 distributions and non-response rates. The third section evaluates data quality of new census questions or questions that have changed substantially: same-sex married couples, ethnic origins, levels of schooling, location where highest diploma was obtained, school attendance, permission to access income tax files, and permission to make personal data publicly available 92 years after the census. The last section summarizes the overall results for questions whose content was coded and evaluated as part of the 2004 test, namely industry, occupation and place of work variables.

    Release date: 2006-03-21

  • Journals and periodicals: 11F0026M
    Description: The Economic Analysis Methodology Paper Series circulates information on definitions employed, standards used, procedures followed and evaluations of the quality of the economic statistics produced by the System of National Accounts (SNA). These papers can be downloaded free at www.statcan.gc.ca.
    Release date: 2005-08-30

  • Journals and periodicals: 92-395-X
    Description:

    This report describes sampling and weighting procedures used in the 2001 Census. It reviews the history of these procedures in Canadian censuses, provides operational and theoretical justifications for them, and presents the results of the evaluation studies of these procedures.

    Release date: 2004-12-15
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