Survey design
Results
All (9)
All (9) ((9 results))
- Articles and reports: 12-001-X201900200003Description:
Merging available sources of information is becoming increasingly important for improving estimates of population characteristics in a variety of fields. In presence of several independent probability samples from a finite population we investigate options for a combined estimator of the population total, based on either a linear combination of the separate estimators or on the combined sample approach. A linear combination estimator based on estimated variances can be biased as the separate estimators of the population total can be highly correlated to their respective variance estimators. We illustrate the possibility to use the combined sample to estimate the variances of the separate estimators, which results in general pooled variance estimators. These pooled variance estimators use all available information and have potential to significantly reduce bias of a linear combination of separate estimators.
Release date: 2019-06-27 - 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: 11-522-X200600110453Description:
National Food and Nutrition Surveys provide critical information to support the understanding the complex relationship between health and diet in the population. Many of these surveys use 24 hour recall methodology which collects at a detailed level all food and beverages consumed over a day. Often it is the longer term intake of foods and nutrients that is of interest and a number of techniques are available that allow estimation of population usual intakes. These techniques require that at least one repeat 24 hour recall be collected from at least a subset of the population in order to estimate the intra individual variability of intakes. Deciding on the number of individuals required to provide a repeat is an important step in the survey design that must recognize that too few repeat individuals compromises the ability to estimate usual intakes, but large numbers of repeats are costly and pose added burden to the respondents. This paper looks at the statistical issues related to the number of repeat individuals, assessing the impact of the number of repeaters on the stability and uncertainty in the estimate of intra individual variability and provides guidance on required number of repeat responders .
Release date: 2008-03-17 - Articles and reports: 12-001-X20060029555Description:
Researchers and policy makers often use data from nationally representative probability sample surveys. The number of topics covered by such surveys, and hence the amount of interviewing time involved, have typically increased over the years, resulting in increased costs and respondent burden. A potential solution to this problem is to carefully form subsets of the items in a survey and administer one such subset to each respondent. Designs of this type are called "split-questionnaire" designs or "matrix sampling" designs. The administration of only a subset of the survey items to each respondent in a matrix sampling design creates what can be considered missing data. Multiple imputation (Rubin 1987), a general-purpose approach developed for handling data with missing values, is appealing for the analysis of data from a matrix sample, because once the multiple imputations are created, data analysts can apply standard methods for analyzing complete data from a sample survey. This paper develops and evaluates a method for creating matrix sampling forms, each form containing a subset of items to be administered to randomly selected respondents. The method can be applied in complex settings, including situations in which skip patterns are present. Forms are created in such a way that each form includes items that are predictive of the excluded items, so that subsequent analyses based on multiple imputation can recover some of the information about the excluded items that would have been collected had there been no matrix sampling. The matrix sampling and multiple-imputation methods are evaluated using data from the National Health and Nutrition Examination Survey, one of many nationally representative probability sample surveys conducted by the National Center for Health Statistics, Centers for Disease Control and Prevention. The study demonstrates the feasibility of the approach applied to a major national health survey with complex structure, and it provides practical advice about appropriate items to include in matrix sampling designs in future surveys.
Release date: 2006-12-21 - Articles and reports: 12-001-X20030016611Description:
Optimal and approximately optimal fixed-cost Bayesian sampling designs are considered for simultaneous estimation in independent homogeneous Poisson processes. General allocation formulae are developed for a basic Poisson-Gamma model and these are compared with more traditional allocation methods. Techniques for finding representative gamma priors under more general hierarchical models are also discussed. The techniques show that, in many practical situations, these gamma priors provide reasonable approximations to the hierarchical prior and Bayes risk. The methods developed are general enough to apply to a wide variety of models and are not limited to Poisson processes.
Release date: 2003-07-31 - 6. Using national registrations to correct for selective non-response: political preference of ethnic groups ArchivedArticles and reports: 11-522-X20010016268Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
This paper deals with non-response bias, discussing a few approaches in this field. It is demonstrated that non-response bias as to voter turnout is lower in a survey on living conditions than in a purely political survey. In addition, auxiliary information from registrations is used to investigate non-response and its bias among ethnic groups. Response rates among ethnic minority groups are rather low, but there is no evidence that response rates are less in lower social class areas. Correcting for limited socioeconomic deviations does not affect the distributions of political preference.
Release date: 2002-09-12 - Articles and reports: 12-001-X19970013107Description:
Often one of the key objectives of multi-purpose demographic surveys in the U.S. is to produce estimates for small domains of the population such as race, ethnicity, and income. Geographic-based oversampling is one of the techniques often considered for improving the reliability of the small domain statistics using block or block group information from the Bureau of the Census to identify areas where the small domains are concentrated. This paper reviews the issues involved in oversampling geographical areas in conjunction with household screening to improve the precision of small domain estimates. The results from an empirical evaluation of the variance reduction from geographic-based oversampling are given along with an assessment of the robustness of the sampling efficiency over time as information for stratification becomes out of date. The simultaneous oversampling of several small domains is also discussed.
Release date: 1997-08-18 - 8. Stability measures for variance component estimators under a stratified multistage design ArchivedArticles and reports: 12-001-X19960022982Description:
In work with sample surveys, we often use estimators of the variance components associated with sampling within and between primary sample units. For these applications, it can be important to have some indication of whether the variance component estimators are stable, i.e., have relatively low variance. This paper discusses several data-based measures of the stability of design-based variance component estimators and related quantities. The development emphasizes methods that can be applied to surveys with moderate or large numbers of strata and small numbers of primary sample units per stratum. We direct principal attention toward the design variance of a within-PSU variance estimator, and two related degrees-of-freedom terms. A simulation-based method allows one to assess whether an observed stability measure is consistent with standard assumptions regarding variance estimator stability. We also develop two sets of stability measures for design-based estimators of between-PSU variance components and the ratio of the overall variance to the within-PSU variance. The proposed methods are applied to interview and examination data from the U.S. Third National Health and Nutrition Examination Survey (NHANES III). These results indicate that the true stability properties may vary substantially across variables. In addition, for some variables, within-PSU variance estimators appear to be considerably less stable than one would anticipate from a simple count of secondary units within each stratum.
Release date: 1997-01-30 - 9. Sample design of the 1988 National Farm Survey ArchivedArticles and reports: 12-001-X199000114553Description:
The National Farm Survey is a sample survey which produces annual estimates on a variety of subjects related to agriculture in Canada. The 1988 survey was conducted using a new sample design. This design involved multiple sampling frames and multivariate sampling techniques different from those of the previous design. This article first describes the strategy and methods used to develop the new sample design, then gives details on factors affecting the precision of the estimates. Finally, the performance of the new design is assessed using the 1988 survey results.
Release date: 1990-06-15
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Analysis (9)
Analysis (9) ((9 results))
- Articles and reports: 12-001-X201900200003Description:
Merging available sources of information is becoming increasingly important for improving estimates of population characteristics in a variety of fields. In presence of several independent probability samples from a finite population we investigate options for a combined estimator of the population total, based on either a linear combination of the separate estimators or on the combined sample approach. A linear combination estimator based on estimated variances can be biased as the separate estimators of the population total can be highly correlated to their respective variance estimators. We illustrate the possibility to use the combined sample to estimate the variances of the separate estimators, which results in general pooled variance estimators. These pooled variance estimators use all available information and have potential to significantly reduce bias of a linear combination of separate estimators.
Release date: 2019-06-27 - 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: 11-522-X200600110453Description:
National Food and Nutrition Surveys provide critical information to support the understanding the complex relationship between health and diet in the population. Many of these surveys use 24 hour recall methodology which collects at a detailed level all food and beverages consumed over a day. Often it is the longer term intake of foods and nutrients that is of interest and a number of techniques are available that allow estimation of population usual intakes. These techniques require that at least one repeat 24 hour recall be collected from at least a subset of the population in order to estimate the intra individual variability of intakes. Deciding on the number of individuals required to provide a repeat is an important step in the survey design that must recognize that too few repeat individuals compromises the ability to estimate usual intakes, but large numbers of repeats are costly and pose added burden to the respondents. This paper looks at the statistical issues related to the number of repeat individuals, assessing the impact of the number of repeaters on the stability and uncertainty in the estimate of intra individual variability and provides guidance on required number of repeat responders .
Release date: 2008-03-17 - Articles and reports: 12-001-X20060029555Description:
Researchers and policy makers often use data from nationally representative probability sample surveys. The number of topics covered by such surveys, and hence the amount of interviewing time involved, have typically increased over the years, resulting in increased costs and respondent burden. A potential solution to this problem is to carefully form subsets of the items in a survey and administer one such subset to each respondent. Designs of this type are called "split-questionnaire" designs or "matrix sampling" designs. The administration of only a subset of the survey items to each respondent in a matrix sampling design creates what can be considered missing data. Multiple imputation (Rubin 1987), a general-purpose approach developed for handling data with missing values, is appealing for the analysis of data from a matrix sample, because once the multiple imputations are created, data analysts can apply standard methods for analyzing complete data from a sample survey. This paper develops and evaluates a method for creating matrix sampling forms, each form containing a subset of items to be administered to randomly selected respondents. The method can be applied in complex settings, including situations in which skip patterns are present. Forms are created in such a way that each form includes items that are predictive of the excluded items, so that subsequent analyses based on multiple imputation can recover some of the information about the excluded items that would have been collected had there been no matrix sampling. The matrix sampling and multiple-imputation methods are evaluated using data from the National Health and Nutrition Examination Survey, one of many nationally representative probability sample surveys conducted by the National Center for Health Statistics, Centers for Disease Control and Prevention. The study demonstrates the feasibility of the approach applied to a major national health survey with complex structure, and it provides practical advice about appropriate items to include in matrix sampling designs in future surveys.
Release date: 2006-12-21 - Articles and reports: 12-001-X20030016611Description:
Optimal and approximately optimal fixed-cost Bayesian sampling designs are considered for simultaneous estimation in independent homogeneous Poisson processes. General allocation formulae are developed for a basic Poisson-Gamma model and these are compared with more traditional allocation methods. Techniques for finding representative gamma priors under more general hierarchical models are also discussed. The techniques show that, in many practical situations, these gamma priors provide reasonable approximations to the hierarchical prior and Bayes risk. The methods developed are general enough to apply to a wide variety of models and are not limited to Poisson processes.
Release date: 2003-07-31 - 6. Using national registrations to correct for selective non-response: political preference of ethnic groups ArchivedArticles and reports: 11-522-X20010016268Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
This paper deals with non-response bias, discussing a few approaches in this field. It is demonstrated that non-response bias as to voter turnout is lower in a survey on living conditions than in a purely political survey. In addition, auxiliary information from registrations is used to investigate non-response and its bias among ethnic groups. Response rates among ethnic minority groups are rather low, but there is no evidence that response rates are less in lower social class areas. Correcting for limited socioeconomic deviations does not affect the distributions of political preference.
Release date: 2002-09-12 - Articles and reports: 12-001-X19970013107Description:
Often one of the key objectives of multi-purpose demographic surveys in the U.S. is to produce estimates for small domains of the population such as race, ethnicity, and income. Geographic-based oversampling is one of the techniques often considered for improving the reliability of the small domain statistics using block or block group information from the Bureau of the Census to identify areas where the small domains are concentrated. This paper reviews the issues involved in oversampling geographical areas in conjunction with household screening to improve the precision of small domain estimates. The results from an empirical evaluation of the variance reduction from geographic-based oversampling are given along with an assessment of the robustness of the sampling efficiency over time as information for stratification becomes out of date. The simultaneous oversampling of several small domains is also discussed.
Release date: 1997-08-18 - 8. Stability measures for variance component estimators under a stratified multistage design ArchivedArticles and reports: 12-001-X19960022982Description:
In work with sample surveys, we often use estimators of the variance components associated with sampling within and between primary sample units. For these applications, it can be important to have some indication of whether the variance component estimators are stable, i.e., have relatively low variance. This paper discusses several data-based measures of the stability of design-based variance component estimators and related quantities. The development emphasizes methods that can be applied to surveys with moderate or large numbers of strata and small numbers of primary sample units per stratum. We direct principal attention toward the design variance of a within-PSU variance estimator, and two related degrees-of-freedom terms. A simulation-based method allows one to assess whether an observed stability measure is consistent with standard assumptions regarding variance estimator stability. We also develop two sets of stability measures for design-based estimators of between-PSU variance components and the ratio of the overall variance to the within-PSU variance. The proposed methods are applied to interview and examination data from the U.S. Third National Health and Nutrition Examination Survey (NHANES III). These results indicate that the true stability properties may vary substantially across variables. In addition, for some variables, within-PSU variance estimators appear to be considerably less stable than one would anticipate from a simple count of secondary units within each stratum.
Release date: 1997-01-30 - 9. Sample design of the 1988 National Farm Survey ArchivedArticles and reports: 12-001-X199000114553Description:
The National Farm Survey is a sample survey which produces annual estimates on a variety of subjects related to agriculture in Canada. The 1988 survey was conducted using a new sample design. This design involved multiple sampling frames and multivariate sampling techniques different from those of the previous design. This article first describes the strategy and methods used to develop the new sample design, then gives details on factors affecting the precision of the estimates. Finally, the performance of the new design is assessed using the 1988 survey results.
Release date: 1990-06-15
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