Statistical techniques
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- Articles and reports: 11-522-X202200100008Description: The publication of more disaggregated data can increase transparency and provide important information on underrepresented groups. Developing more readily available access options increases the amount of information available to and produced by researchers. Increasing the breadth and depth of the information released allows for a better representation of the Canadian population, but also puts a greater responsibility on Statistics Canada to do this in a way that preserves confidentiality, and thus it is helpful to develop tools which allow Statistics Canada to quantify the risk from the additional data granularity. In an effort to evaluate the risk of a database reconstruction attack on Statistics Canada’s published Census data, this investigation follows the strategy of the US Census Bureau, who outlined a method to use a Boolean satisfiability (SAT) solver to reconstruct individual attributes of residents of a hypothetical US Census block, based just on a table of summary statistics. The technique is expanded to attempt to reconstruct a small fraction of Statistics Canada’s Census microdata. This paper will discuss the findings of the investigation, the challenges involved in mounting a reconstruction attack, and the effect of an existing confidentiality measure in mitigating these attacks. Furthermore, the existing strategy is compared to other potential methods used to protect data – in particular, releasing tabular data perturbed by some random mechanism, such as those suggested by differential privacy.Release date: 2024-03-25
- Articles and reports: 11-633-X2019002Description:
Survey data collection through mobile devices, such as tablets and smartphones, is underway in Canada. However, little is known about the representativeness of the data collected through these devices. In March 2017, Statistics Canada commissioned survey data collection through the Carrot Rewards Application and included 11 questions on the Carrot Rewards Mobile App Survey (Carrot) drawn from the 2017 Canadian Community Health Survey (CCHS).
Release date: 2019-06-04 - Surveys and statistical programs – Documentation: 85-602-XDescription:
The purpose of this report is to provide an overview of existing methods and techniques making use of personal identifiers to support record linkage. Record linkage can be loosely defined as a methodology for manipulating and / or transforming personal identifiers from individual data records from one or more operational databases and subsequently attempting to match these personal identifiers to create a composite record about an individual. Record linkage is not intended to uniquely identify individuals for operational purposes; however, it does provide probabilistic matches of varying degrees of reliability for use in statistical reporting. Techniques employed in record linkage may also be of use for investigative purposes to help narrow the field of search against existing databases when some form of personal identification information exists.
Release date: 2000-12-05 - Journals and periodicals: 84F0013XGeography: Canada, Province or territoryDescription:
This study was initiated to test the validity of probabilistic linkage methods used at Statistics Canada. It compared the results of data linkages on infant deaths in Canada with infant death data from Nova Scotia and Alberta. It also compared the availability of fetal deaths on the national and provincial files.
Release date: 1999-10-08 - Articles and reports: 12-001-X199300214459Description:
Record linkage is the matching of records containing data on individuals, businesses or dwellings when a unique identifier is not available. Methods used in practice involve classification of record pairs as links and non-links using an automated procedure based on the theoretical framework introduced by Fellegi and Sunter (1969). The estimation of classification error rates is an important issue. Fellegi and Sunter provide a method for calculation of classification error rate estimates as a direct by-product of linkage. These model-based estimates are easier to produce than the estimates based on manual matching of samples that are typically used in practice. Properties of model-based classification error rate estimates obtained using three estimators of model parameters are compared.
Release date: 1993-12-15 - 6. Alternative socio-economic data collection methods in the 1980’s: The concept of a synthetic data base ArchivedArticles and reports: 12-001-X198000254947Description: This paper makes a proposal to create a new type of information bank, the “Synthetic Data Bank”. This type of bank would involve linking information from two data banks to create a third. The result would be that much greater use could be made of existing data banks in conjunction with new data collection activities. This would mean a significant reduction in the amount of data to be collected which, in effect, could potentially reduce both data collection costs and response burden. The paper suggests a number of considerations in developing statistical techniques to facilitate the creation of such an information linkage concept. Some of these techniques are to be found in modern literature’ others may well have to be developed.Release date: 1980-12-15
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- Articles and reports: 11-522-X202200100008Description: The publication of more disaggregated data can increase transparency and provide important information on underrepresented groups. Developing more readily available access options increases the amount of information available to and produced by researchers. Increasing the breadth and depth of the information released allows for a better representation of the Canadian population, but also puts a greater responsibility on Statistics Canada to do this in a way that preserves confidentiality, and thus it is helpful to develop tools which allow Statistics Canada to quantify the risk from the additional data granularity. In an effort to evaluate the risk of a database reconstruction attack on Statistics Canada’s published Census data, this investigation follows the strategy of the US Census Bureau, who outlined a method to use a Boolean satisfiability (SAT) solver to reconstruct individual attributes of residents of a hypothetical US Census block, based just on a table of summary statistics. The technique is expanded to attempt to reconstruct a small fraction of Statistics Canada’s Census microdata. This paper will discuss the findings of the investigation, the challenges involved in mounting a reconstruction attack, and the effect of an existing confidentiality measure in mitigating these attacks. Furthermore, the existing strategy is compared to other potential methods used to protect data – in particular, releasing tabular data perturbed by some random mechanism, such as those suggested by differential privacy.Release date: 2024-03-25
- Articles and reports: 11-633-X2019002Description:
Survey data collection through mobile devices, such as tablets and smartphones, is underway in Canada. However, little is known about the representativeness of the data collected through these devices. In March 2017, Statistics Canada commissioned survey data collection through the Carrot Rewards Application and included 11 questions on the Carrot Rewards Mobile App Survey (Carrot) drawn from the 2017 Canadian Community Health Survey (CCHS).
Release date: 2019-06-04 - Journals and periodicals: 84F0013XGeography: Canada, Province or territoryDescription:
This study was initiated to test the validity of probabilistic linkage methods used at Statistics Canada. It compared the results of data linkages on infant deaths in Canada with infant death data from Nova Scotia and Alberta. It also compared the availability of fetal deaths on the national and provincial files.
Release date: 1999-10-08 - Articles and reports: 12-001-X199300214459Description:
Record linkage is the matching of records containing data on individuals, businesses or dwellings when a unique identifier is not available. Methods used in practice involve classification of record pairs as links and non-links using an automated procedure based on the theoretical framework introduced by Fellegi and Sunter (1969). The estimation of classification error rates is an important issue. Fellegi and Sunter provide a method for calculation of classification error rate estimates as a direct by-product of linkage. These model-based estimates are easier to produce than the estimates based on manual matching of samples that are typically used in practice. Properties of model-based classification error rate estimates obtained using three estimators of model parameters are compared.
Release date: 1993-12-15 - 5. Alternative socio-economic data collection methods in the 1980’s: The concept of a synthetic data base ArchivedArticles and reports: 12-001-X198000254947Description: This paper makes a proposal to create a new type of information bank, the “Synthetic Data Bank”. This type of bank would involve linking information from two data banks to create a third. The result would be that much greater use could be made of existing data banks in conjunction with new data collection activities. This would mean a significant reduction in the amount of data to be collected which, in effect, could potentially reduce both data collection costs and response burden. The paper suggests a number of considerations in developing statistical techniques to facilitate the creation of such an information linkage concept. Some of these techniques are to be found in modern literature’ others may well have to be developed.Release date: 1980-12-15
Reference (1)
Reference (1) ((1 result))
- Surveys and statistical programs – Documentation: 85-602-XDescription:
The purpose of this report is to provide an overview of existing methods and techniques making use of personal identifiers to support record linkage. Record linkage can be loosely defined as a methodology for manipulating and / or transforming personal identifiers from individual data records from one or more operational databases and subsequently attempting to match these personal identifiers to create a composite record about an individual. Record linkage is not intended to uniquely identify individuals for operational purposes; however, it does provide probabilistic matches of varying degrees of reliability for use in statistical reporting. Techniques employed in record linkage may also be of use for investigative purposes to help narrow the field of search against existing databases when some form of personal identification information exists.
Release date: 2000-12-05
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