Survey design
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- Articles and reports: 12-001-X202300200016Description: In this discussion, I will present some additional aspects of three major areas of survey theory developed or studied by Jean-Claude Deville: calibration, balanced sampling and the generalized weight-share method.Release date: 2024-01-03
- Articles and reports: 75F0002M2023005Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and systems used to produce income estimates with the release of its 2021 reference year estimates. This paper describes the changes and presents the approximate net result of these changes on income estimates using data for 2019 and 2020. The changes described in this paper highlight the ways in which data quality has been improved while producing minimal impact on key CIS estimates and trends.Release date: 2023-08-29
- Surveys and statistical programs – Documentation: 11-522-X201700014749Description:
As part of the Tourism Statistics Program redesign, Statistics Canada is developing the National Travel Survey (NTS) to collect travel information from Canadian travellers. This new survey will replace the Travel Survey of Residents of Canada and the Canadian resident component of the International Travel Survey. The NTS will take advantage of Statistics Canada’s common sampling frames and common processing tools while maximizing the use of administrative data. This paper discusses the potential uses of administrative data such as Passport Canada files, Canada Border Service Agency files and Canada Revenue Agency files, to increase the efficiency of the NTS sample design.
Release date: 2016-03-24 - Articles and reports: 12-001-X201500214230Description:
This paper develops allocation methods for stratified sample surveys where composite small area estimators are a priority, and areas are used as strata. Longford (2006) proposed an objective criterion for this situation, based on a weighted combination of the mean squared errors of small area means and a grand mean. Here, we redefine this approach within a model-assisted framework, allowing regressor variables and a more natural interpretation of results using an intra-class correlation parameter. We also consider several uses of power allocation, and allow the placing of other constraints such as maximum relative root mean squared errors for stratum estimators. We find that a simple power allocation can perform very nearly as well as the optimal design even when the objective is to minimize Longford’s (2006) criterion.
Release date: 2015-12-17 - Articles and reports: 12-001-X201400214090Description:
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 - Articles and reports: 11-522-X201300014286Description:
The Étude Longitudinale Française depuis l’Enfance (ELFE) [French longitudinal study from childhood on], which began in 2011, involves over 18,300 infants whose parents agreed to participate when they were in the maternity hospital. This cohort survey, which will track the children from birth to adulthood, covers the many aspects of their lives from the perspective of social science, health and environmental health. In randomly selected maternity hospitals, all infants in the target population, who were born on one of 25 days distributed across the four seasons, were chosen. This sample is the outcome of a non-standard sampling scheme that we call product sampling. In this survey, it takes the form of the cross-tabulation between two independent samples: a sampling of maternity hospitals and a sampling of days. While it is easy to imagine a cluster effect due to the sampling of maternity hospitals, one can also imagine a cluster effect due to the sampling of days. The scheme’s time dimension therefore cannot be ignored if the desired estimates are subject to daily or seasonal variation. While this non-standard scheme can be viewed as a particular kind of two-phase design, it needs to be defined within a more specific framework. Following a comparison of the product scheme with a conventional two-stage design, we propose variance estimators specially formulated for this sampling scheme. Our ideas are illustrated with a simulation study.
Release date: 2014-10-31 - Articles and reports: 12-001-X201300111824Description:
In most surveys all sample units receive the same treatment and the same design features apply to all selected people and households. In this paper, it is explained how survey designs may be tailored to optimize quality given constraints on costs. Such designs are called adaptive survey designs. The basic ingredients of such designs are introduced, discussed and illustrated with various examples.
Release date: 2013-06-28 - Articles and reports: 12-001-X201200111682Description:
Sample allocation issues are studied in the context of estimating sub-population (stratum or domain) means as well as the aggregate population mean under stratified simple random sampling. A non-linear programming method is used to obtain "optimal" sample allocation to strata that minimizes the total sample size subject to specified tolerances on the coefficient of variation of the estimators of strata means and the population mean. The resulting total sample size is then used to determine sample allocations for the methods of Costa, Satorra and Ventura (2004) based on compromise allocation and Longford (2006) based on specified "inferential priorities". In addition, we study sample allocation to strata when reliability requirements for domains, cutting across strata, are also specified. Performance of the three methods is studied using data from Statistics Canada's Monthly Retail Trade Survey (MRTS) of single establishments.
Release date: 2012-06-27 - 9. Stratified balanced sampling ArchivedArticles and reports: 12-001-X200900110888Description:
In the selection of a sample, a current practice is to define a sampling design stratified on subpopulations. This reduces the variance of the Horvitz-Thompson estimator in comparison with direct sampling if the strata are highly homogeneous with respect to the variable of interest. If auxiliary variables are available for each individual, sampling can be improved through balanced sampling within each stratum, and the Horvitz-Thompson estimator will be more precise if the auxiliary variables are strongly correlated with the variable of interest. However, if the sample allocation is small in some strata, balanced sampling will be only very approximate. In this paper, we propose a method of selecting a sample that is balanced across the entire population while maintaining a fixed allocation within each stratum. We show that in the important special case of size-2 sampling in each stratum, the precision of the Horvitz-Thompson estimator is improved if the variable of interest is well explained by balancing variables over the entire population. An application to rotational sampling is also presented.
Release date: 2009-06-22 - Articles and reports: 12-001-X200800110618Description:
The National Health and Nutrition Examination Survey (NHANES) is one of a series of health-related programs sponsored by the United States National Center for Health Statistics. A unique feature of NHANES is the administration of a complete medical examination for each respondent in the sample. To standardize administration, these examinations are carried out in mobile examination centers. The examination includes physical measurements, tests such as eye and dental examinations, and the collection of blood and urine specimens for laboratory testing. NHANES is an ongoing annual health survey of the noninstitutionalized civilian population of the United States. The major analytic goals of NHANES include estimating the number and percentage of persons in the U.S. population and in designated subgroups with selected diseases and risk factors. The sample design for NHANES must create a balance between the requirements for efficient annual and multiyear samples and the flexibility that allows changes in key design parameters to make the survey more responsive to the needs of the research and health policy communities. This paper discusses the challenges involved in designing and implementing a sample selection process that satisfies the goals of NHANES.
Release date: 2008-06-26
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- Articles and reports: 12-001-X202300200016Description: In this discussion, I will present some additional aspects of three major areas of survey theory developed or studied by Jean-Claude Deville: calibration, balanced sampling and the generalized weight-share method.Release date: 2024-01-03
- Articles and reports: 75F0002M2023005Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and systems used to produce income estimates with the release of its 2021 reference year estimates. This paper describes the changes and presents the approximate net result of these changes on income estimates using data for 2019 and 2020. The changes described in this paper highlight the ways in which data quality has been improved while producing minimal impact on key CIS estimates and trends.Release date: 2023-08-29
- Articles and reports: 12-001-X201500214230Description:
This paper develops allocation methods for stratified sample surveys where composite small area estimators are a priority, and areas are used as strata. Longford (2006) proposed an objective criterion for this situation, based on a weighted combination of the mean squared errors of small area means and a grand mean. Here, we redefine this approach within a model-assisted framework, allowing regressor variables and a more natural interpretation of results using an intra-class correlation parameter. We also consider several uses of power allocation, and allow the placing of other constraints such as maximum relative root mean squared errors for stratum estimators. We find that a simple power allocation can perform very nearly as well as the optimal design even when the objective is to minimize Longford’s (2006) criterion.
Release date: 2015-12-17 - Articles and reports: 12-001-X201400214090Description:
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 - Articles and reports: 11-522-X201300014286Description:
The Étude Longitudinale Française depuis l’Enfance (ELFE) [French longitudinal study from childhood on], which began in 2011, involves over 18,300 infants whose parents agreed to participate when they were in the maternity hospital. This cohort survey, which will track the children from birth to adulthood, covers the many aspects of their lives from the perspective of social science, health and environmental health. In randomly selected maternity hospitals, all infants in the target population, who were born on one of 25 days distributed across the four seasons, were chosen. This sample is the outcome of a non-standard sampling scheme that we call product sampling. In this survey, it takes the form of the cross-tabulation between two independent samples: a sampling of maternity hospitals and a sampling of days. While it is easy to imagine a cluster effect due to the sampling of maternity hospitals, one can also imagine a cluster effect due to the sampling of days. The scheme’s time dimension therefore cannot be ignored if the desired estimates are subject to daily or seasonal variation. While this non-standard scheme can be viewed as a particular kind of two-phase design, it needs to be defined within a more specific framework. Following a comparison of the product scheme with a conventional two-stage design, we propose variance estimators specially formulated for this sampling scheme. Our ideas are illustrated with a simulation study.
Release date: 2014-10-31 - Articles and reports: 12-001-X201300111824Description:
In most surveys all sample units receive the same treatment and the same design features apply to all selected people and households. In this paper, it is explained how survey designs may be tailored to optimize quality given constraints on costs. Such designs are called adaptive survey designs. The basic ingredients of such designs are introduced, discussed and illustrated with various examples.
Release date: 2013-06-28 - Articles and reports: 12-001-X201200111682Description:
Sample allocation issues are studied in the context of estimating sub-population (stratum or domain) means as well as the aggregate population mean under stratified simple random sampling. A non-linear programming method is used to obtain "optimal" sample allocation to strata that minimizes the total sample size subject to specified tolerances on the coefficient of variation of the estimators of strata means and the population mean. The resulting total sample size is then used to determine sample allocations for the methods of Costa, Satorra and Ventura (2004) based on compromise allocation and Longford (2006) based on specified "inferential priorities". In addition, we study sample allocation to strata when reliability requirements for domains, cutting across strata, are also specified. Performance of the three methods is studied using data from Statistics Canada's Monthly Retail Trade Survey (MRTS) of single establishments.
Release date: 2012-06-27 - 8. Stratified balanced sampling ArchivedArticles and reports: 12-001-X200900110888Description:
In the selection of a sample, a current practice is to define a sampling design stratified on subpopulations. This reduces the variance of the Horvitz-Thompson estimator in comparison with direct sampling if the strata are highly homogeneous with respect to the variable of interest. If auxiliary variables are available for each individual, sampling can be improved through balanced sampling within each stratum, and the Horvitz-Thompson estimator will be more precise if the auxiliary variables are strongly correlated with the variable of interest. However, if the sample allocation is small in some strata, balanced sampling will be only very approximate. In this paper, we propose a method of selecting a sample that is balanced across the entire population while maintaining a fixed allocation within each stratum. We show that in the important special case of size-2 sampling in each stratum, the precision of the Horvitz-Thompson estimator is improved if the variable of interest is well explained by balancing variables over the entire population. An application to rotational sampling is also presented.
Release date: 2009-06-22 - Articles and reports: 12-001-X200800110618Description:
The National Health and Nutrition Examination Survey (NHANES) is one of a series of health-related programs sponsored by the United States National Center for Health Statistics. A unique feature of NHANES is the administration of a complete medical examination for each respondent in the sample. To standardize administration, these examinations are carried out in mobile examination centers. The examination includes physical measurements, tests such as eye and dental examinations, and the collection of blood and urine specimens for laboratory testing. NHANES is an ongoing annual health survey of the noninstitutionalized civilian population of the United States. The major analytic goals of NHANES include estimating the number and percentage of persons in the U.S. population and in designated subgroups with selected diseases and risk factors. The sample design for NHANES must create a balance between the requirements for efficient annual and multiyear samples and the flexibility that allows changes in key design parameters to make the survey more responsive to the needs of the research and health policy communities. This paper discusses the challenges involved in designing and implementing a sample selection process that satisfies the goals of NHANES.
Release date: 2008-06-26 - Articles and reports: 11-522-X200600110427Description:
The National Health and Nutrition Examination Surveys (NHANES) is one of a series of health-related programs sponsored by the United States National Center for Health Statistics. A unique feature of NHANES is the administration of a complete medical examination for each respondent in the sample. To standardize administration, these examinations are carried out in mobile examination centers (MECs). The examination includes physical measurements, tests such as eye and dental examinations, and the collection of blood and urine specimens for laboratory testing. NHANES is an ongoing annual health survey of the noninstitutionalized civilian population of the United States. The major analytic goals of NHANES include estimating the number and percentage of persons in the U.S. population and in designated subgroups with selected diseases and risk factors. The sample design for NHANES needs to create a balance between the requirements for efficient annual and multiyear samples and the flexibility that allows changes in key design parameters to make the survey more responsive to the needs of the research and health policy communities. This paper discusses the challenges involved in designing and implementing a sample selection process that satisfies the goals of NHANES.
Release date: 2008-03-17
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Reference (2) ((2 results))
- Surveys and statistical programs – Documentation: 11-522-X201700014749Description:
As part of the Tourism Statistics Program redesign, Statistics Canada is developing the National Travel Survey (NTS) to collect travel information from Canadian travellers. This new survey will replace the Travel Survey of Residents of Canada and the Canadian resident component of the International Travel Survey. The NTS will take advantage of Statistics Canada’s common sampling frames and common processing tools while maximizing the use of administrative data. This paper discusses the potential uses of administrative data such as Passport Canada files, Canada Border Service Agency files and Canada Revenue Agency files, to increase the efficiency of the NTS sample design.
Release date: 2016-03-24 - Surveys and statistical programs – Documentation: 11-522-X20010016225Description:
The European Union Labour Forces Survey (LFS) is based on national surveys that were originally very different. For the past decade, under pressure from increasingly demanding users (particularly with respect to timeliness, comparability and flexibility), the LFS has been subjected to a constant process of quality improvement.
The following topics are presented in this paper:A. the quality improvement process, which comprises screening national survey methods, target structure, legal foundations, quality reports, more accurate and more explicit definitions of components, etc.;B. expected or achieved results, which include an ongoing survey producing quarterly results within reasonable time frames, comparable employment and unemployment rates over time and space in more than 25 countries, specific information on current political topics, etc.;C. continuing shortcomings, such as implementation delays in certain countries, possibilities of longitudinal analysis, public access to microdata, etc.; D. future tasks envisioned, such as adaptation of the list of ISCO and ISCED variables and nomenclatures (to take into account evolution in employment and teaching methods), differential treatment of structural variables and increased recourse to administrative files (to limit respondent burden), harmonization of questionnaires, etc.
Release date: 2002-09-12
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