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All (2,299) (30 to 40 of 2,299 results)

  • 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

  • Articles and reports: 11-633-X2024001
    Description: The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 35 years.
    Release date: 2024-01-22

  • Articles and reports: 13-604-M2024001
    Description: This documentation outlines the methodology used to develop the Distributions of household economic accounts published in January 2024 for the reference years 2010 to 2023. It describes the framework and the steps implemented to produce distributional information aligned with the National Balance Sheet Accounts and other national accounts concepts. It also includes a report on the quality of the estimated distributions.
    Release date: 2024-01-22

  • Journals and periodicals: 11-633-X
    Description: 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

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

  • Articles and reports: 12-001-X202300200001
    Description: 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-X202300200002
    Description: Being able to quantify the accuracy (bias, variance) of published output is crucial in official statistics. Output in official statistics is nearly always divided into subpopulations according to some classification variable, such as mean income by categories of educational level. Such output is also referred to as domain statistics. In the current paper, we limit ourselves to binary classification variables. In practice, misclassifications occur and these contribute to the bias and variance of domain statistics. Existing analytical and numerical methods to estimate this effect have two disadvantages. The first disadvantage is that they require that the misclassification probabilities are known beforehand and the second is that the bias and variance estimates are biased themselves. In the current paper we present a new method, a Gaussian mixture model estimated by an Expectation-Maximisation (EM) algorithm combined with a bootstrap, referred to as the EM bootstrap method. This new method does not require that the misclassification probabilities are known beforehand, although it is more efficient when a small audit sample is used that yields a starting value for the misclassification probabilities in the EM algorithm. We compared the performance of the new method with currently available numerical methods: the bootstrap method and the SIMEX method. Previous research has shown that for non-linear parameters the bootstrap outperforms the analytical expressions. For nearly all conditions tested, the bias and variance estimates that are obtained by the EM bootstrap method are closer to their true values than those obtained by the bootstrap and SIMEX methods. We end this paper by discussing the results and possible future extensions of the method.
    Release date: 2024-01-03

  • Articles and reports: 12-001-X202300200003
    Description: We investigate small area prediction of general parameters based on two models for unit-level counts. We construct predictors of parameters, such as quartiles, that may be nonlinear functions of the model response variable. We first develop a procedure to construct empirical best predictors and mean square error estimators of general parameters under a unit-level gamma-Poisson model. We then use a sampling importance resampling algorithm to develop predictors for a generalized linear mixed model (GLMM) with a Poisson response distribution. We compare the two models through simulation and an analysis of data from the Iowa Seat-Belt Use Survey.
    Release date: 2024-01-03

  • Articles and reports: 12-001-X202300200004
    Description: 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: 12-001-X202300200005
    Description: Population undercoverage is one of the main hurdles faced by statistical analysis with non-probability survey samples. We discuss two typical scenarios of undercoverage, namely, stochastic undercoverage and deterministic undercoverage. We argue that existing estimation methods under the positivity assumption on the propensity scores (i.e., the participation probabilities) can be directly applied to handle the scenario of stochastic undercoverage. We explore strategies for mitigating biases in estimating the mean of the target population under deterministic undercoverage. In particular, we examine a split population approach based on a convex hull formulation, and construct estimators with reduced biases. A doubly robust estimator can be constructed if a followup subsample of the reference probability survey with measurements on the study variable becomes feasible. Performances of six competing estimators are investigated through a simulation study and issues which require further investigation are briefly discussed.
    Release date: 2024-01-03
Data (9)

Data (9) ((9 results))

No content available at this time.

Analysis (1,874)

Analysis (1,874) (1,870 to 1,880 of 1,874 results)

  • Articles and reports: 12-001-X197800154829
    Description:

    This paper advances the case that administrative records are a powerful source of statistics and in support of this conclusion provides an overview of the extensive utilization in Canada of administrative records for statistical purposes. The paper discusses recent developments and the changing environment which are seen as major determinants of both the creation of administrative data bases as well as their utilization. The capabilities of the computer, combined with the extensive demand for statistics and the limited financial resources available to meet that demand, are seen as combining to lead to more extensive use of administrative records. A variety of problems associated with the use of administrative records is specified and the development of strategies to meet these problems and permit utilization of administrative records is described. Recent developments in Canada intended to support the use of administrative records are indicated.

    Release date: 1978-06-15

  • Articles and reports: 12-001-X197700254828
    Description:

    Non-response exists in any survey, but its magnitude depends upon the type of survey, the interviewers’ ability to conduct an interview, and the respondents’ motivation to respond to survey questions. This paper discusses non-response in relation to a number of household surveys and in particular the behaviour of non-response rates over time in a continuous survey such as the Canadian Labour Force Survey.

    A profile of interviewers employed by Statistics Canada shows that the correlation between non-response and a number of interviewer characteristics is not significant. Respondents themselves, and their motivation, are the key elements in an interview process and therefore in respondent relations.

    This article draws on the results of various studies conducted to investigate the effects of response burden, choice of respondent and response incentives to provide some insight into the characteristics of non-respondents.

    Release date: 1977-12-15

  • Articles and reports: 12-001-X197500254824
    Description:

    Madow [1968] has proposed a two-phase sampling scheme under which response bias can be eliminated from sample surveys by obtaining “true” values for a subsample of the original sample. Often in cases of Censuses or ongoing surveys, the subsample data are not used to correct the main survey estimates but to assess their reliability. The main purpose of this paper is to present methods by which reliability estimates can be obtained when true values can be determined for a subsample of units.

    Release date: 1975-12-15

  • Articles and reports: 12-001-X197500254825
    Description:

    Random rounding is a technique to ensure confidentiality of aggregate statistics. By randomly rounding all the components of a total, independently, together with the random rounding of the total itself, substantial discrepancies may arise when aggregating the published data. This paper presents a procedure which avoids substantial discrepancies while still protecting the concept of confidentiality.

    Release date: 1975-12-15
Reference (363)

Reference (363) (0 to 10 of 363 results)

  • Notices and consultations: 13-605-X
    Description: This product contains articles related to the latest methodological, conceptual developments in the Canadian System of Macroeconomic Accounts as well as the analysis of the Canadian economy. It includes articles detailing new methods, concepts and statistical techniques used to compile the Canadian System of Macroeconomic Accounts. It also includes information related to new or expanded data products, provides updates and supplements to information found in various guides and analytical articles touching upon a broad range of topics related to the Canadian economy.
    Release date: 2024-02-29

  • Surveys and statistical programs – Documentation: 32-26-0007
    Description: Census of Agriculture data provide statistical information on farms and farm operators at fine geographic levels and for small subpopulations. Quality evaluation activities are essential to ensure that census data are reliable and that they meet user needs.

    This report provides data quality information pertaining to the Census of Agriculture, such as sources of error, error detection, disclosure control methods, data quality indicators, response rates and collection rates.
    Release date: 2024-02-06

  • Surveys and statistical programs – Documentation: 75-005-M2023001
    Description: This document provides information on the evolution of response rates for the Labour Force Survey (LFS) and a discussion of the evaluation of two aspects of data quality that ensure the LFS estimates continue providing an accurate portrait of the Canadian labour market.
    Release date: 2023-10-30

  • Surveys and statistical programs – Documentation: 98-306-X
    Description:

    This report describes sampling, weighting and estimation procedures used in the Census of Population. It provides operational and theoretical justifications for them, and presents the results of the evaluations of these procedures.

    Release date: 2023-10-04

  • Surveys and statistical programs – Documentation: 84-538-X
    Geography: Canada
    Description: This electronic publication presents the methodology underlying the production of the life tables for Canada, provinces and territories.
    Release date: 2023-08-28

  • Surveys and statistical programs – Documentation: 32-26-0006
    Description: This report provides data quality information pertaining to the Agriculture–Population Linkage, such as sources of error, matching process, response rates, imputation rates, sampling, weighting, disclosure control methods and data quality indicators.
    Release date: 2023-08-25

  • Surveys and statistical programs – Documentation: 75-514-G
    Description: The Guide to the Job Vacancy and Wage Survey contains a dictionary of concepts and definitions, and covers topics such as survey methodology, data collection, processing, and data quality. The guide covers both components of the survey: the job vacancy component, which is quarterly, and the wage component, which is annual.
    Release date: 2023-05-25

  • Surveys and statistical programs – Documentation: 32-26-0002
    Description:

    This reference guide may be useful to both new and experienced users who wish to familiarize themselves with and find specific information about the Census of Agriculture.

    It provides an overview of the Census of Agriculture communications, content determination, collection, processing, data quality evaluation and dissemination activities. It also summarizes the key changes to the census and other useful information.

    Release date: 2022-04-14

  • Geographic files and documentation: 12-572-X
    Description:

    The Standard Geographical Classification (SGC) provides a systematic classification structure that categorizes all of the geographic area of Canada. The SGC is the official classification used in the Census of Population and other Statistics Canada surveys.

    The classification is organized in two volumes: Volume I, The Classification and Volume II, Reference Maps.

    Volume II contains reference maps showing boundaries, names, codes and locations of the geographic areas in the classification. The reference maps show census subdivisions, census divisions, census metropolitan areas, census agglomerations, census metropolitan influenced zones and economic regions. Definitions for these terms are found in Volume I, The Classification. Volume I describes the classification and related standard geographic areas and place names.

    The maps in Volume II can be downloaded in PDF format from our website.

    Release date: 2022-02-09

  • Surveys and statistical programs – Documentation: 12-004-X
    Description:

    Statistics: Power from Data! is a web resource that was created in 2001 to assist secondary students and teachers of Mathematics and Information Studies in getting the most from statistics. Over the past 20 years, this product has become one of Statistics Canada most popular references for students, teachers, and many other members of the general population. This product was last updated in 2021.

    Release date: 2021-09-02

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