Collection and questionnaires
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- Articles and reports: 89-648-X2016001Description:
Linkages between survey and administrative data are an increasingly common practice, due in part to the reduced burden to respondents, and to the data that can be obtained at a relatively low cost. Historical linkage, or the linkage of administrative data from previous years to the year of the survey, compounds these benefits by providing additional years of data. This paper examines the Longitudinal and International Study of Adults (LISA), which was linked to historical tax data on personal income tax returns (T1) and those collected from employers’ files (T4), among others not mentioned in this paper. It presents trends in historical linkage rates, compares the coherence of administrative data between the T1 and T4, presents the ability to use the data to create balanced panels, and uses the T1 data to produce age-earnings profiles by sex. The results show that the historical linkage rate is high (over 90% in most cases) and stable over time for respondents who are likely to file a tax return, and that the T1 and T4 administrative sources show similar earnings. Moreover, long balanced panels of up to 30 years in length (at the time of writing) can be created using LISA administrative linkage data.
Release date: 2016-08-18 - Notices and consultations: 92-140-X2016001Description:
The 2016 Census Program Content Test was conducted from May 2 to June 30, 2014. The Test was designed to assess the impact of any proposed content changes to the 2016 Census Program and to measure the impact of including a social insurance number (SIN) question on the data quality.
This quantitative test used a split-panel design involving 55,000 dwellings, divided into 11 panels of 5,000 dwellings each: five panels were dedicated to the Content Test while the remaining six panels were for the SIN Test. Two models of test questionnaires were developed to meet the objectives, namely a model with all the proposed changes EXCEPT the SIN question and a model with all the proposed changes INCLUDING the SIN question. A third model of 'control' questionnaire with the 2011 content was also developed. The population living in a private dwelling in mail-out areas in one of the ten provinces was targeted for the test. Paper and electronic response channels were part of the Test as well.
This report presents the Test objectives, the design and a summary of the analysis in order to determine potential content for the 2016 Census Program. Results from the data analysis of the Test were not the only elements used to determine the content for 2016. Other elements were also considered, such as response burden, comparison over time and users’ needs.
Release date: 2016-04-01 - Surveys and statistical programs – Documentation: 11-522-X201700014706Description:
Over the last decade, Statistics Canada’s Producer Prices Division has expanded its service producer price indexes program and continued to improve its goods and construction producer price indexes program. While the majority of price indexes are based on traditional survey methods, efforts were made to increase the use of administrative data and alternative data sources in order to reduce burden on our respondents. This paper focuses mainly on producer price programs, but also provides information on the growing importance of alternative data sources at Statistics Canada. In addition, it presents the operational challenges and risks that statistical offices could face when relying more and more on third-party outputs. Finally, it presents the tools being developed to integrate alternative data while collecting metadata.
Release date: 2016-03-24 - 4. Challenges and results in using Audit trail data to monitor Labour Force Survey data quality ArchivedSurveys and statistical programs – Documentation: 11-522-X201700014707Description:
The Labour Force Survey (LFS) is a monthly household survey of about 56,000 households that provides information on the Canadian labour market. Audit Trail is a Blaise programming option, for surveys like LFS with Computer Assisted Interviewing (CAI), which creates files containing every keystroke and edit and timestamp of every data collection attempt on all households. Combining such a large survey with such a complete source of paradata opens the door to in-depth data quality analysis but also quickly leads to Big Data challenges. How can meaningful information be extracted from this large set of keystrokes and timestamps? How can it help assess the quality of LFS data collection? The presentation will describe some of the challenges that were encountered, solutions that were used to address them, and results of the analysis on data quality.
Release date: 2016-03-24 - 5. Road Congestion Measures Using Instantaneous Information From the Canadian Vehicle Use Study (CVUS) ArchivedArticles and reports: 11-522-X201700014709Description:
Traffic congestion is not limited to large cities but is also becoming a problem in medium-size cities and to roads going through cities. Among a large variety of congestion measures, six were selected for the ease of aggregation and their capacity to use the instantaneous information from CVUS-light component in 2014. From the selected measures, the Index of Congestion is potentially the only one not biased. This measure is used to illustrate different dimension of congestion on the road network.
Release date: 2016-03-24 - Articles and reports: 11-522-X201700014744Description:
This presentation will begin with Dr. West providing a summary of research that has been conducted on the quality and utility of paradata collected as part of the United States National Survey of Family Growth (NSFG). The NSFG is the major national fertility survey in the U.S., and an important source of data on sexual activity, sexual behavior, and reproductive health for policy makers. For many years, the NSFG has been collecting various forms of paradata, including keystroke information (e.g., Couper and Kreuter 2013), call record information, detailed case disposition information, and interviewer observations related to key NSFG measures (e.g., West 2013). Dr. West will discuss some of the challenges of working with these data, in addition to evidence of their utility for nonresponse adjustment, interviewer evaluation, and/or responsive survey design purposes. Dr. Kreuter will then present research done using paradata collected as part of two panel surveys: the Medical Expenditure Panel Survey (MEPS) in the United States, and the Panel Labour Market and Social Security (PASS) in Germany. In both surveys, information from contacts in prior waves were experimentally used to improve contact and response rates in subsequent waves. In addition, research from PASS will be presented where interviewer observations on key outcome variables were collected to be used in nonresponse adjustment or responsive survey design decisions. Dr. Kreuter will not only present the research results but also the practical challenges in implementing the collection and use of both sets of paradata.
Release date: 2016-03-24 - Articles and reports: 11-522-X201700014746Description:
Paradata research has focused on identifying opportunities for strategic improvement in data collection that could be operationally viable and lead to enhancements in quality or cost efficiency. To that end, Statistics Canada has developed and implemented a responsive collection design (RCD) strategy for computer-assisted telephone interview (CATI) household surveys to maximize quality and efficiency and to potentially reduce costs. RCD is an adaptive approach to survey data collection that uses information available prior to and during data collection to adjust the collection strategy for the remaining in-progress cases. In practice, the survey managers monitor and analyze collection progress against a predetermined set of indicators for two purposes: to identify critical data-collection milestones that require significant changes to the collection approach and to adjust collection strategies to make the most efficient use of remaining available resources. In the RCD context, numerous considerations come into play when determining which aspects of data collection to adjust and how to adjust them. Paradata sources play a key role in the planning, development and implementation of active management for RCD surveys. Since 2009, Statistics Canada has conducted several RCD surveys. This paper describes Statistics Canada’s experiences in implementing and monitoring this type of surveys.
Release date: 2016-03-24 - Surveys and statistical programs – Documentation: 11-522-X201700014751Description:
Practically all major retailers use scanners to record the information on their transactions with clients (consumers). These data normally include the product code, a brief description, the price and the quantity sold. This is an extremely relevant data source for statistical programs such as Statistics Canada’s Consumer Price Index (CPI), one of Canada’s most important economic indicators. Using scanner data could improve the quality of the CPI by increasing the number of prices used in calculations, expanding geographic coverage and including the quantities sold, among other things, while lowering data collection costs. However, using these data presents many challenges. An examination of scanner data from a first retailer revealed a high rate of change in product identification codes over a one-year period. The effects of these changes pose challenges from a product classification and estimate quality perspective. This article focuses on the issues associated with acquiring, classifying and examining these data to assess their quality for use in the CPI.
Release date: 2016-03-24 - Articles and reports: 11-522-X201700014752Description:
This paper presents a new price index method for processing electronic transaction (scanner) data. Price indices are calculated as a ratio of a turnover index and a weighted quantity index. Product weights of quantities sold are computed from the deflated prices of each month in the current publication year. New products can be timely incorporated without price imputations, so that all transactions can be processed. Product weights are monthly updated and are used to calculate direct indices with respect to a fixed base month. Price indices are free of chain drift by this construction. The results are robust under departures from the methodological choices. The method is part of the Dutch CPI since January 2016, when it was first applied to mobile phones.
Release date: 2016-03-24 - 10. A look into the future ArchivedArticles and reports: 11-522-X201700014753Description:
The fact that the world is in continuous change and that new technologies are becoming widely available creates new opportunities and challenges for National Statistical Institutes (NSIs) worldwide. What if NSIs could access vast amounts of sophisticated data for free (or for a low cost) from enterprises? Could this facilitate the possibility for NSIs to disseminate more accurate indicators for the policy-makers and users, significantly reduce the response burden for companies, reduce costs for the NSIs and in the long run improve the living standards of the people in a country? The time has now come for NSIs to find the best practice to align legislation, regulations and practices in relation to scanner data and big data. Without common ground, the prospect of reaching consensus is unlikely. The discussions need to start with how to define quality. If NSIs define and approach quality differently, this will lead to a highly undesirable situation, as NSIs will move further away from harmonisation. Sweden was one of the leading countries that put these issues on the agenda for European cooperation; in 2012 Sweden implemented scanner data in the national Consumer Price Index after it was proven through research studies and statistical analyses that scanner data was significantly better than the manually collected data.
Release date: 2016-03-24
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- Articles and reports: 89-648-X2016001Description:
Linkages between survey and administrative data are an increasingly common practice, due in part to the reduced burden to respondents, and to the data that can be obtained at a relatively low cost. Historical linkage, or the linkage of administrative data from previous years to the year of the survey, compounds these benefits by providing additional years of data. This paper examines the Longitudinal and International Study of Adults (LISA), which was linked to historical tax data on personal income tax returns (T1) and those collected from employers’ files (T4), among others not mentioned in this paper. It presents trends in historical linkage rates, compares the coherence of administrative data between the T1 and T4, presents the ability to use the data to create balanced panels, and uses the T1 data to produce age-earnings profiles by sex. The results show that the historical linkage rate is high (over 90% in most cases) and stable over time for respondents who are likely to file a tax return, and that the T1 and T4 administrative sources show similar earnings. Moreover, long balanced panels of up to 30 years in length (at the time of writing) can be created using LISA administrative linkage data.
Release date: 2016-08-18 - 2. Road Congestion Measures Using Instantaneous Information From the Canadian Vehicle Use Study (CVUS) ArchivedArticles and reports: 11-522-X201700014709Description:
Traffic congestion is not limited to large cities but is also becoming a problem in medium-size cities and to roads going through cities. Among a large variety of congestion measures, six were selected for the ease of aggregation and their capacity to use the instantaneous information from CVUS-light component in 2014. From the selected measures, the Index of Congestion is potentially the only one not biased. This measure is used to illustrate different dimension of congestion on the road network.
Release date: 2016-03-24 - Articles and reports: 11-522-X201700014744Description:
This presentation will begin with Dr. West providing a summary of research that has been conducted on the quality and utility of paradata collected as part of the United States National Survey of Family Growth (NSFG). The NSFG is the major national fertility survey in the U.S., and an important source of data on sexual activity, sexual behavior, and reproductive health for policy makers. For many years, the NSFG has been collecting various forms of paradata, including keystroke information (e.g., Couper and Kreuter 2013), call record information, detailed case disposition information, and interviewer observations related to key NSFG measures (e.g., West 2013). Dr. West will discuss some of the challenges of working with these data, in addition to evidence of their utility for nonresponse adjustment, interviewer evaluation, and/or responsive survey design purposes. Dr. Kreuter will then present research done using paradata collected as part of two panel surveys: the Medical Expenditure Panel Survey (MEPS) in the United States, and the Panel Labour Market and Social Security (PASS) in Germany. In both surveys, information from contacts in prior waves were experimentally used to improve contact and response rates in subsequent waves. In addition, research from PASS will be presented where interviewer observations on key outcome variables were collected to be used in nonresponse adjustment or responsive survey design decisions. Dr. Kreuter will not only present the research results but also the practical challenges in implementing the collection and use of both sets of paradata.
Release date: 2016-03-24 - Articles and reports: 11-522-X201700014746Description:
Paradata research has focused on identifying opportunities for strategic improvement in data collection that could be operationally viable and lead to enhancements in quality or cost efficiency. To that end, Statistics Canada has developed and implemented a responsive collection design (RCD) strategy for computer-assisted telephone interview (CATI) household surveys to maximize quality and efficiency and to potentially reduce costs. RCD is an adaptive approach to survey data collection that uses information available prior to and during data collection to adjust the collection strategy for the remaining in-progress cases. In practice, the survey managers monitor and analyze collection progress against a predetermined set of indicators for two purposes: to identify critical data-collection milestones that require significant changes to the collection approach and to adjust collection strategies to make the most efficient use of remaining available resources. In the RCD context, numerous considerations come into play when determining which aspects of data collection to adjust and how to adjust them. Paradata sources play a key role in the planning, development and implementation of active management for RCD surveys. Since 2009, Statistics Canada has conducted several RCD surveys. This paper describes Statistics Canada’s experiences in implementing and monitoring this type of surveys.
Release date: 2016-03-24 - Articles and reports: 11-522-X201700014752Description:
This paper presents a new price index method for processing electronic transaction (scanner) data. Price indices are calculated as a ratio of a turnover index and a weighted quantity index. Product weights of quantities sold are computed from the deflated prices of each month in the current publication year. New products can be timely incorporated without price imputations, so that all transactions can be processed. Product weights are monthly updated and are used to calculate direct indices with respect to a fixed base month. Price indices are free of chain drift by this construction. The results are robust under departures from the methodological choices. The method is part of the Dutch CPI since January 2016, when it was first applied to mobile phones.
Release date: 2016-03-24 - 6. A look into the future ArchivedArticles and reports: 11-522-X201700014753Description:
The fact that the world is in continuous change and that new technologies are becoming widely available creates new opportunities and challenges for National Statistical Institutes (NSIs) worldwide. What if NSIs could access vast amounts of sophisticated data for free (or for a low cost) from enterprises? Could this facilitate the possibility for NSIs to disseminate more accurate indicators for the policy-makers and users, significantly reduce the response burden for companies, reduce costs for the NSIs and in the long run improve the living standards of the people in a country? The time has now come for NSIs to find the best practice to align legislation, regulations and practices in relation to scanner data and big data. Without common ground, the prospect of reaching consensus is unlikely. The discussions need to start with how to define quality. If NSIs define and approach quality differently, this will lead to a highly undesirable situation, as NSIs will move further away from harmonisation. Sweden was one of the leading countries that put these issues on the agenda for European cooperation; in 2012 Sweden implemented scanner data in the national Consumer Price Index after it was proven through research studies and statistical analyses that scanner data was significantly better than the manually collected data.
Release date: 2016-03-24
Reference (5)
Reference (5) ((5 results))
- Notices and consultations: 92-140-X2016001Description:
The 2016 Census Program Content Test was conducted from May 2 to June 30, 2014. The Test was designed to assess the impact of any proposed content changes to the 2016 Census Program and to measure the impact of including a social insurance number (SIN) question on the data quality.
This quantitative test used a split-panel design involving 55,000 dwellings, divided into 11 panels of 5,000 dwellings each: five panels were dedicated to the Content Test while the remaining six panels were for the SIN Test. Two models of test questionnaires were developed to meet the objectives, namely a model with all the proposed changes EXCEPT the SIN question and a model with all the proposed changes INCLUDING the SIN question. A third model of 'control' questionnaire with the 2011 content was also developed. The population living in a private dwelling in mail-out areas in one of the ten provinces was targeted for the test. Paper and electronic response channels were part of the Test as well.
This report presents the Test objectives, the design and a summary of the analysis in order to determine potential content for the 2016 Census Program. Results from the data analysis of the Test were not the only elements used to determine the content for 2016. Other elements were also considered, such as response burden, comparison over time and users’ needs.
Release date: 2016-04-01 - Surveys and statistical programs – Documentation: 11-522-X201700014706Description:
Over the last decade, Statistics Canada’s Producer Prices Division has expanded its service producer price indexes program and continued to improve its goods and construction producer price indexes program. While the majority of price indexes are based on traditional survey methods, efforts were made to increase the use of administrative data and alternative data sources in order to reduce burden on our respondents. This paper focuses mainly on producer price programs, but also provides information on the growing importance of alternative data sources at Statistics Canada. In addition, it presents the operational challenges and risks that statistical offices could face when relying more and more on third-party outputs. Finally, it presents the tools being developed to integrate alternative data while collecting metadata.
Release date: 2016-03-24 - 3. Challenges and results in using Audit trail data to monitor Labour Force Survey data quality ArchivedSurveys and statistical programs – Documentation: 11-522-X201700014707Description:
The Labour Force Survey (LFS) is a monthly household survey of about 56,000 households that provides information on the Canadian labour market. Audit Trail is a Blaise programming option, for surveys like LFS with Computer Assisted Interviewing (CAI), which creates files containing every keystroke and edit and timestamp of every data collection attempt on all households. Combining such a large survey with such a complete source of paradata opens the door to in-depth data quality analysis but also quickly leads to Big Data challenges. How can meaningful information be extracted from this large set of keystrokes and timestamps? How can it help assess the quality of LFS data collection? The presentation will describe some of the challenges that were encountered, solutions that were used to address them, and results of the analysis on data quality.
Release date: 2016-03-24 - Surveys and statistical programs – Documentation: 11-522-X201700014751Description:
Practically all major retailers use scanners to record the information on their transactions with clients (consumers). These data normally include the product code, a brief description, the price and the quantity sold. This is an extremely relevant data source for statistical programs such as Statistics Canada’s Consumer Price Index (CPI), one of Canada’s most important economic indicators. Using scanner data could improve the quality of the CPI by increasing the number of prices used in calculations, expanding geographic coverage and including the quantities sold, among other things, while lowering data collection costs. However, using these data presents many challenges. An examination of scanner data from a first retailer revealed a high rate of change in product identification codes over a one-year period. The effects of these changes pose challenges from a product classification and estimate quality perspective. This article focuses on the issues associated with acquiring, classifying and examining these data to assess their quality for use in the CPI.
Release date: 2016-03-24 - Surveys and statistical programs – Documentation: 89-654-X2016003Description:
This paper describes the process that led to the creation of the new Disability Screening Questions (DSQ), jointly developped by Statistics Canada and Employment and Social Development Canada. The DSQ form a new module which can be put on general population surveys to allow comparisons of persons with and without a disability. The paper explains why there are two versions of the DSQ—a long and a short one—, the difference between the two, and how each version can be used.
Release date: 2016-02-29
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