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1. Labour Force Survey initiatives under Statistics Canada’s Disaggregated Data Action Plan Archived
Articles and reports: 11-522-X202200100004
Description: In accordance with Statistics Canada’s long-term Disaggregated Data Action Plan (DDAP), several initiatives have been implemented into the Labour Force Survey (LFS). One of the more direct initiatives was a targeted increase in the size of the monthly LFS sample. Furthermore, a regular Supplement program was introduced, where an additional series of questions are asked to a subset of LFS respondents and analyzed in a monthly or quarterly production cycle. Finally, the production of modelled estimates based on Small Area Estimation (SAE) methodologies resumed for the LFS and will include a wider scope with more analytical value than what had existed in the past. This paper will give an overview of these three initiatives.
Release date: 2024-03-25
2. ABS DataLab output checking tools Archived
Articles and reports: 11-522-X202200100006
Description: The Australian Bureau of Statistics (ABS) is committed to improving access to more microdata, while ensuring privacy and confidentiality is maintained, through its virtual DataLab which supports researchers to undertake complex research more efficiently. Currently, the DataLab research outputs need to follow strict rules to minimise disclosure risks for clearance. However, the clerical-review process is not cost effective and has potential to introduce errors. The increasing number of statistical outputs from different projects can potentially introduce differencing risks even though these outputs from different projects have met the strict output rules. The ABS has been exploring the possibility of providing automatic output checking using the ABS cellkey methodology to ensure that all outputs across different projects are protected consistently to minimise differencing risks and reduce costs associated with output checking.
Release date: 2024-03-25
3. Toward a system of integrated statistical data on education and training Archived
Articles and reports: 11-522-X202200100009
Description: Education and training is acknowledged as fundamental for the development of a society. It is a complex multidimensional phenomenon, which determinants are ascribable to several interrelated familiar and socio-economic conditions. To respond to the demand of supporting statistical information for policymaking and its monitoring and evaluation process, the Italian National Statistical Institute (Istat) is renewing the education and training statistical production system, implementing a new thematic statistical register. It will be part of the Istat Integrated System of Registers, thus allowing relating the education and training phenomenon to other relevant phenomena, e.g. transition to work.
Release date: 2024-03-25
4. Gender-based Analysis Plus: Optimizing data disaggregation and analysis
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
5. Statistical Methodology Research and Development Program Achievements
Journals and periodicals: 12-206-X
Description: 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
6. Methods for Constructing Life Tables for Canada, Provinces and Territories
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
7. Agriculture–Population Linkage: Data quality report
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
8. Low-income concepts and statistics, 2021 Census of Population
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
9. Canadian Statistical Geospatial Explorer Hub Archived
Data Visualization: 71-607-X2020010
Description: The Canadian Statistical Geospatial Explorer empowers users to discover geo enabled data holdings of Statistics Canada at various levels of geography including at the neighbourhood level. Users are able to visualize, thematically map, spatially explore and analyze, export and consume data in various formats. Users can also view the data superimposed on satellite imagery, topographic and street layers.
Release date: 2023-01-24
10. Investigating the Use of Blockchain to Authenticate Data from the Statistics Canada Website
Articles and reports: 11-633-X2022007
Description:
This paper investigates how Statistics Canada can increase trust by giving users the ability to authenticate data from its website through digital signatures and blockchain technology.

Release date: 2022-09-19

Data (1)

Data (1) ((1 result))

1. Canadian Statistical Geospatial Explorer Hub Archived
Data Visualization: 71-607-X2020010
Description: The Canadian Statistical Geospatial Explorer empowers users to discover geo enabled data holdings of Statistics Canada at various levels of geography including at the neighbourhood level. Users are able to visualize, thematically map, spatially explore and analyze, export and consume data in various formats. Users can also view the data superimposed on satellite imagery, topographic and street layers.
Release date: 2023-01-24

Analysis (78)

Analysis (78) (20 to 30 of 78 results)

21. Estimation methods on multiple sampling frames in two-stage sample designs Archived
Articles and reports: 12-001-X201400214090
Description:
When studying a finite population, it is sometimes necessary to select samples from several sampling frames in order to represent all individuals. Here we are interested in the scenario where two samples are selected using a two-stage design, with common first-stage selection. We apply the Hartley (1962), Bankier (1986) and Kalton and Anderson (1986) methods, and we show that these methods can be applied conditional on first-stage selection. We also compare the performance of several estimators as part of a simulation study. Our results suggest that the estimator should be chosen carefully when there are multiple sampling frames, and that a simple estimator is sometimes preferable, even if it uses only part of the information collected.
Release date: 2014-12-19
22. Frequentist and Bayesian approaches for comparing interviewer variance components in two groups of survey interviewers Archived
Articles and reports: 12-001-X201400214092
Description:
Survey methodologists have long studied the effects of interviewers on the variance of survey estimates. Statistical models including random interviewer effects are often fitted in such investigations, and research interest lies in the magnitude of the interviewer variance component. One question that might arise in a methodological investigation is whether or not different groups of interviewers (e.g., those with prior experience on a given survey vs. new hires, or CAPI interviewers vs. CATI interviewers) have significantly different variance components in these models. Significant differences may indicate a need for additional training in particular subgroups, or sub-optimal properties of different modes or interviewing styles for particular survey items (in terms of the overall mean squared error of survey estimates). Survey researchers seeking answers to these types of questions have different statistical tools available to them. This paper aims to provide an overview of alternative frequentist and Bayesian approaches to the comparison of variance components in different groups of survey interviewers, using a hierarchical generalized linear modeling framework that accommodates a variety of different types of survey variables. We first consider the benefits and limitations of each approach, contrasting the methods used for estimation and inference. We next present a simulation study, empirically evaluating the ability of each approach to efficiently estimate differences in variance components. We then apply the two approaches to an analysis of real survey data collected in the U.S. National Survey of Family Growth (NSFG). We conclude that the two approaches tend to result in very similar inferences, and we provide suggestions for practice given some of the subtle differences observed.
Release date: 2014-12-19
23. Weighted estimation and bootstrap variance estimation for analyzing survey data: How to implement in selected software Archived
Articles and reports: 12-002-X201400111901
Description:
This document is for analysts/researchers who are considering doing research with data from a survey where both survey weights and bootstrap weights are provided in the data files. This document gives directions, for some selected software packages, about how to get started in using survey weights and bootstrap weights for an analysis of survey data. We give brief directions for obtaining survey-weighted estimates, bootstrap variance estimates (and other desired error quantities) and some typical test statistics for each software package in turn. While these directions are provided just for the chosen examples, there will be information about the range of weighted and bootstrapped analyses that can be carried out by each software package.
Release date: 2014-08-07
24. Pseudo-likelihood-based Bayesian information criterion for variable selection in survey data Archived
Articles and reports: 12-001-X201300211871
Description:
Regression models are routinely used in the analysis of survey data, where one common issue of interest is to identify influential factors that are associated with certain behavioral, social, or economic indices within a target population. When data are collected through complex surveys, the properties of classical variable selection approaches developed in i.i.d. non-survey settings need to be re-examined. In this paper, we derive a pseudo-likelihood-based BIC criterion for variable selection in the analysis of survey data and suggest a sample-based penalized likelihood approach for its implementation. The sampling weights are appropriately assigned to correct the biased selection result caused by the distortion between the sample and the target population. Under a joint randomization framework, we establish the consistency of the proposed selection procedure. The finite-sample performance of the approach is assessed through analysis and computer simulations based on data from the hypertension component of the 2009 Survey on Living with Chronic Diseases in Canada.
Release date: 2014-01-15
25. Sparse and efficient replication variance estimation for complex surveys Archived
Articles and reports: 12-001-X201300111826
Description:
It is routine practice for survey organizations to provide replication weights as part of survey data files. These replication weights are meant to produce valid and efficient variance estimates for a variety of estimators in a simple and systematic manner. Most existing methods for constructing replication weights, however, are only valid for specific sampling designs and typically require a very large number of replicates. In this paper we first show how to produce replication weights based on the method outlined in Fay (1984) such that the resulting replication variance estimator is algebraically equivalent to the fully efficient linearization variance estimator for any given sampling design. We then propose a novel weight-calibration method to simultaneously achieve efficiency and sparsity in the sense that a small number of sets of replication weights can produce valid and efficient replication variance estimators for key population parameters. Our proposed method can be used in conjunction with existing resampling techniques for large-scale complex surveys. Validity of the proposed methods and extensions to some balanced sampling designs are also discussed. Simulation results showed that our proposed variance estimators perform very well in tracking coverage probabilities of confidence intervals. Our proposed strategies will likely have impact on how public-use survey data files are produced and how these data sets are analyzed.
Release date: 2013-06-28
26. Combining cohorts in longitudinal surveys Archived
Articles and reports: 12-001-X201300111828
Description:
A question that commonly arises in longitudinal surveys is the issue of how to combine differing cohorts of the survey. In this paper we present a novel method for combining different cohorts, and using all available data, in a longitudinal survey to estimate parameters of a semiparametric model, which relates the response variable to a set of covariates. The procedure builds upon the Weighted Generalized Estimation Equation method for handling missing waves in longitudinal studies. Our method is set up under a joint-randomization framework for estimation of model parameters, which takes into account the superpopulation model as well as the survey design randomization. We also propose a design-based, and a joint-randomization, variance estimation method. To illustrate the methodology we apply it to the Survey of Doctorate Recipients, conducted by the U.S. National Science Foundation.
Release date: 2013-06-28
27. Indirect sampling applied to skewed populations Archived
Articles and reports: 12-001-X201300111829
Description:
Indirect Sampling is used when the sampling frame is not the same as the target population, but related to the latter. The estimation process for Indirect Sampling is carried out using the Generalised Weight Share Method (GWSM), which is an unbiased procedure (see Lavallée 2002, 2007). For business surveys, Indirect Sampling is applied as follows: the sampling frame is one of establishments, while the target population is one of enterprises. Enterprises are selected through their establishments. This allows stratifying according to the establishment characteristics, rather than those associated with enterprises. Because the variables of interest of establishments are generally highly skewed (a small portion of the establishments covers the major portion of the economy), the GWSM results in unbiased estimates, but their variance can be large. The purpose of this paper is to suggest some adjustments to the weights to reduce the variance of the estimates in the context of skewed populations, while keeping the method unbiased. After a brief overview of Indirect Sampling and the GWSM, we describe the required adjustments to the GWSM. The estimates produced with these adjustments are compared to those from the original GWSM, via a small numerical example, and using real data originating from the Statistics Canada's Business Register.
Release date: 2013-06-28
28. On the performance of self benchmarked small area estimators under the Fay-Herriot area level model Archived
Articles and reports: 12-001-X201300111830
Description:
We consider two different self-benchmarking methods for the estimation of small area means based on the Fay-Herriot (FH) area level model: the method of You and Rao (2002) applied to the FH model and the method of Wang, Fuller and Qu (2008) based on augmented models. We derive an estimator of the mean squared prediction error (MSPE) of the You-Rao (YR) estimator of a small area mean that, under the true model, is correct to second-order terms. We report the results of a simulation study on the relative bias of the MSPE estimator of the YR estimator and the MSPE estimator of the Wang, Fuller and Qu (WFQ) estimator obtained under an augmented model. We also study the MSPE and the estimators of MSPE for the YR and WFQ estimators obtained under a misspecified model.
Release date: 2013-06-28
29. Conservative variance estimation for sampling designs with zero pairwise inclusion probabilities Archived
Articles and reports: 12-001-X201300111831
Description:
We consider conservative variance estimation for the Horvitz-Thompson estimator of a population total in sampling designs with zero pairwise inclusion probabilities, known as "non-measurable" designs. We decompose the standard Horvitz-Thompson variance estimator under such designs and characterize the bias precisely. We develop a bias correction that is guaranteed to be weakly conservative (nonnegatively biased) regardless of the nature of the non-measurability. The analysis sheds light on conditions under which the standard Horvitz-Thompson variance estimator performs well despite non-measurability and where the conservative bias correction may outperform commonly-used approximations.
Release date: 2013-06-28
30. Survey Quality Archived
Articles and reports: 12-001-X201200211751
Description:
Survey quality is a multi-faceted concept that originates from two different development paths. One path is the total survey error paradigm that rests on four pillars providing principles that guide survey design, survey implementation, survey evaluation, and survey data analysis. We should design surveys so that the mean squared error of an estimate is minimized given budget and other constraints. It is important to take all known error sources into account, to monitor major error sources during implementation, to periodically evaluate major error sources and combinations of these sources after the survey is completed, and to study the effects of errors on the survey analysis. In this context survey quality can be measured by the mean squared error and controlled by observations made during implementation and improved by evaluation studies. The paradigm has both strengths and weaknesses. One strength is that research can be defined by error sources and one weakness is that most total survey error assessments are incomplete in the sense that it is not possible to include the effects of all the error sources. The second path is influenced by ideas from the quality management sciences. These sciences concern business excellence in providing products and services with a focus on customers and competition from other providers. These ideas have had a great influence on many statistical organizations. One effect is the acceptance among data providers that product quality cannot be achieved without a sufficient underlying process quality and process quality cannot be achieved without a good organizational quality. These levels can be controlled and evaluated by service level agreements, customer surveys, paradata analysis using statistical process control, and organizational assessment using business excellence models or other sets of criteria. All levels can be improved by conducting improvement projects chosen by means of priority functions. The ultimate goal of improvement projects is that the processes involved should gradually approach a state where they are error-free. Of course, this might be an unattainable goal, albeit one to strive for. It is not realistic to hope for continuous measurements of the total survey error using the mean squared error. Instead one can hope that continuous quality improvement using management science ideas and statistical methods can minimize biases and other survey process problems so that the variance becomes an approximation of the mean squared error. If that can be achieved we have made the two development paths approximately coincide.
Release date: 2012-12-19

Reference (20)

Reference (20) (0 to 10 of 20 results)

1. Methods for Constructing Life Tables for Canada, Provinces and Territories
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
2. Agriculture–Population Linkage: Data quality report
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
3. Painting a Portrait of Canada: The 2021 Census of Population
Notices and consultations: 98-26-0001
Description:
This white paper presents Statistics Canada’s planned approach to the 2021 Census of Population and provides a clear explanation of the processes behind the census program, touching on historical, legal, operational and content aspects. Statistics Canada recognizes that it is important to not only successfully conduct the census, but also to be transparent and informative about the way in which those efforts are accomplished. Painting a Portrait of Canada: The 2021 Census of Population gives readers an exclusive, detailed look at how census data is collected, analyzed and given back to Canadians, in the form of high-quality statistical information, used to make evidence-based decisions in Canadian society.
Release date: 2020-07-20
4. Analytical Studies Branch Annual Consolidated Plan for Research, Data Development and Modelling, 2019/2020 Archived
Surveys and statistical programs – Documentation: 11-633-X2019001
Description:
The mandate of the Analytical Studies Branch (ASB) is to provide high-quality, relevant and timely information on economic, health and social issues that are important to Canadians. The branch strategically makes use of expert knowledge and a large range of statistical sources to describe, draw inferences from, and make objective and scientifically supported deductions about the evolving nature of the Canadian economy and society. Research questions are addressed by applying leading-edge methods, including microsimulation and predictive analytics using a range of linked and integrated administrative and survey data. In supporting greater access to data, ASB linked data are made available to external researchers and policy makers to support evidence-based decision making. Research results are disseminated by the branch using a range of mediums (i.e., research papers, studies, infographics, videos, and blogs) to meet user needs. The branch also provides analytical support and training, feedback, and quality assurance to the wide range of programs within and outside Statistics Canada.
Release date: 2019-05-29
5. The Research Data Centres Information and Technical Bulletin
Notices and consultations: 12-002-X
Description:
The Research Data Centres (RDCs) Information and Technical Bulletin (ITB) is a forum by which Statistics Canada analysts and the research community can inform each other on survey data uses and methodological techniques. Articles in the ITB focus on data analysis and modelling, data management, and best or ineffective statistical, computational, and scientific practices. Further, ITB topics will include essays on data content, implications of questionnaire wording, comparisons of datasets, reviews on methodologies and their application, data peculiarities, problematic data and solutions, and explanations of innovative tools using RDC surveys and relevant software. All of these essays may provide advice and detailed examples outlining commands, habits, tricks and strategies used to make problem-solving easier for the RDC user.
The main aims of the ITB are:
- the advancement and dissemination of knowledge surrounding Statistics Canada's data; - the exchange of ideas among the RDC-user community;- the support of new users; - the co-operation with subject matter experts and divisions within Statistics Canada.
The ITB is interested in quality articles that are worth publicizing throughout the research community, and that will add value to the quality of research produced at Statistics Canada's RDCs.
Release date: 2015-03-25
6. Teacher's Guide to Data Discovery Archived
Surveys and statistical programs – Documentation: 12-593-X
Description: A guide for elementary and secondary teachers on the basic skills involved in statistical investigation: choosing the dataset, understanding data concepts and analysing the data with or without computer software.
Release date: 2010-09-24
7. Aboriginal Peoples Technical Report, 2006 Census Archived
Surveys and statistical programs – Documentation: 92-569-X
Description:
The 2006 Census Technical Report on Aboriginal Peoples deals with: (i) Aboriginal ancestry, (ii) Aboriginal identity, (iii) registered Indian status, and (iv) First Nation or Band membership. The report aims to inform users about the complexity of the data and any difficulties that could affect their use. It explains the conceptual framework and definitions used to gather the data, and it discusses factors that could affect data quality. The historical comparability of the data is also discussed.
Release date: 2010-02-09
8. Aboriginal Peoples Technical Report, 2006 Census, Second Edition Archived
Surveys and statistical programs – Documentation: 92-569-X2006002
Description:
The 2006 Census Technical Report on Aboriginal Peoples deals with: (i) Aboriginal ancestry, (ii) Aboriginal identity, (iii) registered Indian status, and (iv) First Nation or Band membership. The report aims to inform users about the complexity of the data and any difficulties that could affect their use. It explains the conceptual framework and definitions used to gather the data, and it discusses factors that could affect data quality. The historical comparability of the data is also discussed.
The second edition includes the same content as the first, and new text has been added on data processing (Chapter 3). As well, modified content about data quality and 'on reserve' communities has been incorporated into the original sections.
Release date: 2010-02-09
9. Evaluation of the Strengths and Difficulties Questionnaire Archived
Surveys and statistical programs – Documentation: 89-634-X2009008
Geography: Canada
Description:
The Strengths and Difficulties Questionnaire (SDQ) is a parent-reported instrument designed to provide information on children's behaviours and relationships. The SDQ consists of 25 items which are grouped into five subscales: (1) pro-social, (2) inattention-hyperactivity, (3) emotional symptoms, (4) conduct problems, and (5) peer problems. The SDQ was used to provide information on children aged 2 to 5 years in the 2006 Aboriginal Children's Survey (ACS). Though validated on general populations, the constructs of the SDQ have not been validated for off-reserve First Nations, Métis and Inuit children in Canada. The first objective of this evaluation is to examine if the five subscales of the SDQ demonstrate construct validity and reliability for off-reserve First Nations, Métis and Inuit children. The second objective is to examine if an alternative set of subscales, using the 25 SDQ items, may be more valid and reliable for off-reserve First Nations, Métis and Inuit children.
Release date: 2009-11-25
10. Feasibility Study on the Use of Provincial/Territorial Medicare Records for Measuring the Level of Inter-provincial and Inter-territorial Migration Archived
Surveys and statistical programs – Documentation: 91F0015M2008010
Geography: Canada
Description:
The objective of this study is to examine the feasibility of using provincial and territorial health care files of new registrants as an independent measure of preliminary inter-provincial and inter-territorial migration. The study aims at measuring the conceptual and quantifiable differences between this data source and our present source of the Canada Revenue Agency's Canadian Child Tax Benefit.
Criteria were established to assess the quality and appropriateness of these provincial/territorial health care records as a proxy for our migration estimates: coverage, consistency, timeliness, reliability, level of detail, uniformity and accuracy.
Based on the present analysis, the paper finds that these data do not ameliorate the estimates and would not be suitable at this time as a measure of inter-provincial/territorial migration. These Medicare data though are an important independent data source that can be used for quality evaluation.
Release date: 2009-01-13

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