Keyword search
Filter results by
Search HelpCurrently selected filters that can be removed
Keyword(s)
Subject
- Selected: Statistical methods (52)
- Administrative data (4)
- Collection and questionnaires (3)
- Data analysis (6)
- Disclosure control and data dissemination (2)
- History and context (5)
- Inference and foundations (3)
- Quality assurance (3)
- Response and nonresponse (2)
- Simulations (3)
- Statistical techniques (4)
- Survey design (8)
- Time series (1)
- Weighting and estimation (17)
- Other content related to Statistical methods (4)
Type
6 facets displayed. 0 facets selected.
Survey or statistical program
18 facets displayed. 0 facets selected.
- Gross Domestic Product by Industry - National (Monthly) (1)
- Gross Domestic Product by Industry - Provincial and Territorial (Annual) (1)
- Productivity Measures and Related Variables - National and Provincial (Annual) (1)
- Financial Flow Accounts (1)
- National Balance Sheet Accounts (1)
- National Gross Domestic Product by Income and by Expenditure Accounts (1)
- Provincial and Territorial Gross Domestic Product by Income and by Expenditure Accounts (1)
- Estimates of Labour Income (1)
- Census of Agriculture (1)
- Labour Force Survey (1)
- Survey of Labour and Income Dynamics (1)
- Census of Population (1)
- Annual Income Estimates for Census Families and Individuals (T1 Family File) (1)
- Longitudinal Immigration Database (1)
- Canadian Income Survey (1)
- Canadian Government Finance Statistics (1)
- Canadian Survey on Business Conditions (1)
- Distributions of household economic accounts for wealth of Canadian households (1)
Results
All (52)
All (52) (0 to 10 of 52 results)
- Articles and reports: 75F0002M2024005Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and data sources used to produce income and poverty estimates with the release of its 2022 reference year estimates. Foremost among these improvements is a significant increase in the sample size for a large subset of the CIS content. The weighting methodology was also improved and the target population of the CIS was changed from persons aged 16 years and over to persons aged 15 years and over. This paper describes the changes made and presents the approximate net result of these changes on the income estimates and data quality of the CIS using 2021 data. The changes described in this paper highlight the ways in which data quality has been improved while having little impact on key CIS estimates and trends.Release date: 2024-04-26
- Journals and periodicals: 75F0002MDescription: This series provides detailed documentation on income developments, including survey design issues, data quality evaluation and exploratory research.Release date: 2024-04-26
- 89-26-0006Description: PASSAGES is an open-source dynamic microsimulation model aimed at supporting policy analysis and research relating to Canadian retirement income system outcomes at the individual and family level. The publicly available version includes a synthetic starting database, a model, and documentation. A confidential starting database is also available.Release date: 2024-04-23
- Articles and reports: 18-001-X2024001Description: This study applies small area estimation (SAE) and a new geographic concept called Self-contained Labor Area (SLA) to the Canadian Survey on Business Conditions (CSBC) with a focus on remote work opportunities in rural labor markets. Through SAE modelling, we estimate the proportions of businesses, classified by general industrial sector (service providers and goods producers), that would primarily offer remote work opportunities to their workforce.Release date: 2024-04-22
- Public use microdata: 89F0002XDescription: The SPSD/M is a static microsimulation model designed to analyse financial interactions between governments and individuals in Canada. It can compute taxes paid to and cash transfers received from government. It is comprised of a database, a series of tax/transfer algorithms and models, analytical software and user documentation.Release date: 2024-04-12
- Articles and reports: 11-522-X202200100001Description: Record linkage aims at identifying record pairs related to the same unit and observed in two different data sets, say A and B. Fellegi and Sunter (1969) suggest each record pair is tested whether generated from the set of matched or unmatched pairs. The decision function consists of the ratio between m(y) and u(y),probabilities of observing a comparison y of a set of k>3 key identifying variables in a record pair under the assumptions that the pair is a match or a non-match, respectively. These parameters are usually estimated by means of the EM algorithm using as data the comparisons on all the pairs of the Cartesian product ?=A×B. These observations (on the comparisons and on the pairs status as match or non-match) are assumed as generated independently of other pairs, assumption characterizing most of the literature on record linkage and implemented in software tools (e.g. RELAIS, Cibella et al. 2012). On the contrary, comparisons y and matching status in ? are deterministically dependent. As a result, estimates on m(y) and u(y) based on the EM algorithm are usually bad. This fact jeopardizes the effective application of the Fellegi-Sunter method, as well as automatic computation of quality measures and possibility to apply efficient methods for model estimation on linked data (e.g. regression functions), as in Chambers et al. (2015). We propose to explore ? by a set of samples, each one drawn so to preserve independence of comparisons among the selected record pairs. Simulations are encouraging.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100002Description: The authors used the Splink probabilistic linkage package developed by the UK Ministry of Justice, to link census data from England and Wales to itself to find duplicate census responses. A large gold standard of confirmed census duplicates was available meaning that the results of the Splink implementation could be quality assured. This paper describes the implementation and features of Splink, gives details of the settings and parameters that we used to tune Splink for our particular project, and gives the results that we obtained.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100003Description: Estimation at fine levels of aggregation is necessary to better describe society. Small area estimation model-based approaches that combine sparse survey data with rich data from auxiliary sources have been proven useful to improve the reliability of estimates for small domains. Considered here is a scenario where small area model-based estimates, produced at a given aggregation level, needed to be disaggregated to better describe the social structure at finer levels. For this scenario, an allocation method was developed to implement the disaggregation, overcoming challenges associated with data availability and model development at such fine levels. The method is applied to adult literacy and numeracy estimation at the county-by-group-level, using data from the U.S. Program for the International Assessment of Adult Competencies. In this application the groups are defined in terms of age or education, but the method could be applied to estimation of other equity-deserving groups.Release date: 2024-03-25
- 9. Labour Force Survey initiatives under Statistics Canada’s Disaggregated Data Action Plan ArchivedArticles and reports: 11-522-X202200100004Description: 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
- 10. Application of sampling variance smoothing methods for small area proportion estimation ArchivedArticles and reports: 11-522-X202200100005Description: Sampling variance smoothing is an important topic in small area estimation. In this paper, we propose sampling variance smoothing methods for small area proportion estimation. In particular, we consider the generalized variance function and design effect methods for sampling variance smoothing. We evaluate and compare the smoothed sampling variances and small area estimates based on the smoothed variance estimates through analysis of survey data from Statistics Canada. The results from real data analysis indicate that the proposed sampling variance smoothing methods work very well for small area estimation.Release date: 2024-03-25
Data (1)
Data (1) ((1 result))
- Public use microdata: 89F0002XDescription: The SPSD/M is a static microsimulation model designed to analyse financial interactions between governments and individuals in Canada. It can compute taxes paid to and cash transfers received from government. It is comprised of a database, a series of tax/transfer algorithms and models, analytical software and user documentation.Release date: 2024-04-12
Analysis (48)
Analysis (48) (0 to 10 of 48 results)
- Articles and reports: 75F0002M2024005Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and data sources used to produce income and poverty estimates with the release of its 2022 reference year estimates. Foremost among these improvements is a significant increase in the sample size for a large subset of the CIS content. The weighting methodology was also improved and the target population of the CIS was changed from persons aged 16 years and over to persons aged 15 years and over. This paper describes the changes made and presents the approximate net result of these changes on the income estimates and data quality of the CIS using 2021 data. The changes described in this paper highlight the ways in which data quality has been improved while having little impact on key CIS estimates and trends.Release date: 2024-04-26
- Journals and periodicals: 75F0002MDescription: This series provides detailed documentation on income developments, including survey design issues, data quality evaluation and exploratory research.Release date: 2024-04-26
- Articles and reports: 18-001-X2024001Description: This study applies small area estimation (SAE) and a new geographic concept called Self-contained Labor Area (SLA) to the Canadian Survey on Business Conditions (CSBC) with a focus on remote work opportunities in rural labor markets. Through SAE modelling, we estimate the proportions of businesses, classified by general industrial sector (service providers and goods producers), that would primarily offer remote work opportunities to their workforce.Release date: 2024-04-22
- Articles and reports: 11-522-X202200100001Description: Record linkage aims at identifying record pairs related to the same unit and observed in two different data sets, say A and B. Fellegi and Sunter (1969) suggest each record pair is tested whether generated from the set of matched or unmatched pairs. The decision function consists of the ratio between m(y) and u(y),probabilities of observing a comparison y of a set of k>3 key identifying variables in a record pair under the assumptions that the pair is a match or a non-match, respectively. These parameters are usually estimated by means of the EM algorithm using as data the comparisons on all the pairs of the Cartesian product ?=A×B. These observations (on the comparisons and on the pairs status as match or non-match) are assumed as generated independently of other pairs, assumption characterizing most of the literature on record linkage and implemented in software tools (e.g. RELAIS, Cibella et al. 2012). On the contrary, comparisons y and matching status in ? are deterministically dependent. As a result, estimates on m(y) and u(y) based on the EM algorithm are usually bad. This fact jeopardizes the effective application of the Fellegi-Sunter method, as well as automatic computation of quality measures and possibility to apply efficient methods for model estimation on linked data (e.g. regression functions), as in Chambers et al. (2015). We propose to explore ? by a set of samples, each one drawn so to preserve independence of comparisons among the selected record pairs. Simulations are encouraging.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100002Description: The authors used the Splink probabilistic linkage package developed by the UK Ministry of Justice, to link census data from England and Wales to itself to find duplicate census responses. A large gold standard of confirmed census duplicates was available meaning that the results of the Splink implementation could be quality assured. This paper describes the implementation and features of Splink, gives details of the settings and parameters that we used to tune Splink for our particular project, and gives the results that we obtained.Release date: 2024-03-25
- Articles and reports: 11-522-X202200100003Description: Estimation at fine levels of aggregation is necessary to better describe society. Small area estimation model-based approaches that combine sparse survey data with rich data from auxiliary sources have been proven useful to improve the reliability of estimates for small domains. Considered here is a scenario where small area model-based estimates, produced at a given aggregation level, needed to be disaggregated to better describe the social structure at finer levels. For this scenario, an allocation method was developed to implement the disaggregation, overcoming challenges associated with data availability and model development at such fine levels. The method is applied to adult literacy and numeracy estimation at the county-by-group-level, using data from the U.S. Program for the International Assessment of Adult Competencies. In this application the groups are defined in terms of age or education, but the method could be applied to estimation of other equity-deserving groups.Release date: 2024-03-25
- 7. Labour Force Survey initiatives under Statistics Canada’s Disaggregated Data Action Plan ArchivedArticles and reports: 11-522-X202200100004Description: 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
- Articles and reports: 11-522-X202200100005Description: Sampling variance smoothing is an important topic in small area estimation. In this paper, we propose sampling variance smoothing methods for small area proportion estimation. In particular, we consider the generalized variance function and design effect methods for sampling variance smoothing. We evaluate and compare the smoothed sampling variances and small area estimates based on the smoothed variance estimates through analysis of survey data from Statistics Canada. The results from real data analysis indicate that the proposed sampling variance smoothing methods work very well for small area estimation.Release date: 2024-03-25
- 9. ABS DataLab output checking tools ArchivedArticles and reports: 11-522-X202200100006Description: 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
- Articles and reports: 11-522-X202200100007Description: With the availability of larger and more diverse data sources, Statistical Institutes in Europe are inclined to publish statistics on smaller groups than they used to do. Moreover, high impact global events like the Covid crisis and the situation in Ukraine may also ask for statistics on specific subgroups of the population. Publishing on small, targeted groups not only raises questions on statistical quality of the figures, it also raises issues concerning statistical disclosure risk. The principle of statistical disclosure control does not depend on the size of the groups the statistics are based on. However, the risk of disclosure does depend on the group size: the smaller a group, the higher the risk. Traditional ways to deal with statistical disclosure control and small group sizes include suppressing information and coarsening categories. These methods essentially increase the (mean) group sizes. More recent approaches include perturbative methods that have the intention to keep the group sizes small in order to preserve as much information as possible while reducing the disclosure risk sufficiently. In this paper we will mention some European examples of special focus group statistics and discuss the implications on statistical disclosure control. Additionally, we will discuss some issues that the use of perturbative methods brings along: its impact on disclosure risk and utility as well as the challenges in proper communication thereof.Release date: 2024-03-25
Reference (2)
Reference (2) ((2 results))
- Notices and consultations: 13-605-XDescription: 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: 32-26-0007Description: 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
- Date modified: