Survey design
Results
All (9)
All (9) ((9 results))
- Articles and reports: 12-001-X201100211606Description:
This paper introduces a U.S. Census Bureau special compilation by presenting four other papers of the current issue: three papers from authors Tillé, Lohr and Thompson as well as a discussion paper from Opsomer.
Release date: 2011-12-21 - 2. Adaptive network and spatial sampling ArchivedArticles and reports: 12-001-X201100211607Description:
This paper describes recent developments in adaptive sampling strategies and introduces new variations on those strategies. Recent developments described included targeted random walk designs and adaptive web sampling. These designs are particularly suited for sampling in networks; for example, for finding a sample of people from a hidden human population by following social links from sample individuals to find additional members of the hidden population to add to the sample. Each of these designs can also be translated into spatial settings to produce flexible new spatial adaptive strategies for sampling unevenly distributed populations. Variations on these sampling strategies include versions in which the network or spatial links have unequal weights and are followed with unequal probabilities.
Release date: 2011-12-21 - Articles and reports: 12-001-X201100211608Description:
Designs and estimators for the single frame surveys currently used by U.S. government agencies were developed in response to practical problems. Federal household surveys now face challenges of decreasing response rates and frame coverage, higher data collection costs, and increasing demand for small area statistics. Multiple frame surveys, in which independent samples are drawn from separate frames, can be used to help meet some of these challenges. Examples include combining a list frame with an area frame or using two frames to sample landline telephone households and cellular telephone households. We review point estimators and weight adjustments that can be used to analyze multiple frame surveys with standard survey software, and summarize construction of replicate weights for variance estimation. Because of their increased complexity, multiple frame surveys face some challenges not found in single frame surveys. We investigate misclassification bias in multiple frame surveys, and propose a method for correcting for this bias when misclassification probabilities are known. Finally, we discuss research that is needed on nonsampling errors with multiple frame surveys.
Release date: 2011-12-21 - Articles and reports: 12-001-X201100211609Description:
This paper presents a review and assessment of the use of balanced sampling by means of the cube method. After defining the notion of balanced sample and balanced sampling, a short history of the concept of balancing is presented. The theory of the cube method is briefly presented. Emphasis is placed on the practical problems posed by balanced sampling: the interest of the method with respect to other sampling methods and calibration, the field of application, the accuracy of balancing, the choice of auxiliary variables and ways to implement the method.
Release date: 2011-12-21 - 5. Innovations in survey sampling design: Discussion of three contributions presented at the U.S. Census Bureau ArchivedArticles and reports: 12-001-X201100211610Description:
In this paper, a discussion of the three papers from the US Census Bureau special compilation is presented.
Release date: 2011-12-21 - Articles and reports: 89-648-X2011001Geography: CanadaDescription:
In January 2006, a conference on longitudinal surveys hosted by Statistics Canada, the Social and Humanities Research Council of Canada (SSHRC) and the Canadian Institute of Health Research (CIHR) concluded that Canada lacks a longitudinal survey which collects information on multiple subjects such as family, human capital, labour health and follows respondents for a long period of time. Following this conference, funds were received from the Policy Research Data Gaps fund (PRDG) to support a pilot survey for a new Canadian Household Panel Survey (CHPS-Pilot). Consultations on the design and content were held with academic and policy experts in 2007 and 2008, and a pilot survey was conducted in the fall of 2008. The objectives of the pilot survey were to (1) test a questionnaire, evaluate interview length and measure the quality of data collected, (2) evaluate several design features; and (3) test reactions to the survey from respondents and field workers. The pilot survey achieved a response rate of 76%, with a median household interview time of 64 minutes. Several innovative design features were tested, and found to be viable. Response to the survey, whether from respondents or interviewers, was generally positive. This paper highlights these and other results from the CHPS-Pilot.
Release date: 2011-09-14 - Articles and reports: 12-001-X201100111447Description:
This paper introduces a R-package for the stratification of a survey population using a univariate stratification variable X and for the calculation of stratum sample sizes. Non iterative methods such as the cumulative root frequency method and the geometric stratum boundaries are implemented. Optimal designs, with stratum boundaries that minimize either the CV of the simple expansion estimator for a fixed sample size n or the n value for a fixed CV can be constructed. Two iterative algorithms are available to find the optimal stratum boundaries. The design can feature a user defined certainty stratum where all the units are sampled. Take-all and take-none strata can be included in the stratified design as they might lead to smaller sample sizes. The sample size calculations are based on the anticipated moments of the survey variable Y, given the stratification variable X. The package handles conditional distributions of Y given X that are either a heteroscedastic linear model, or a log-linear model. Stratum specific non-response can be accounted for in the design construction and in the sample size calculations.
Release date: 2011-06-29 - Articles and reports: 12-001-X201100111448Description:
In two-phase sampling for stratification, the second-phase sample is selected by a stratified sample based on the information observed in the first-phase sample. We develop a replication-based bias adjusted variance estimator that extends the method of Kim, Navarro and Fuller (2006). The proposed method is also applicable when the first-phase sampling rate is not negligible and when second-phase sample selection is unequal probability Poisson sampling within each stratum. The proposed method can be extended to variance estimation for two-phase regression estimators. Results from a limited simulation study are presented.
Release date: 2011-06-29 - 9. Cost efficiency of repeated cluster surveys ArchivedArticles and reports: 12-001-X201100111449Description:
We analyze the statistical and economic efficiency of different designs of cluster surveys collected in two consecutive time periods, or waves. In an independent design, two cluster samples in two waves are taken independently from one another. In a cluster-panel design, the same clusters are used in both waves, but samples within clusters are taken independently in two time periods. In an observation-panel design, both clusters and observations are retained from one wave of data collection to another. By assuming a simple population structure, we derive design variances and costs of the surveys conducted according to these designs. We first consider a situation in which the interest lies in estimation of the change in the population mean between two time periods, and derive the optimal sample allocations for the three designs of interest. We then propose the utility maximization framework borrowed from microeconomics to illustrate a possible approach to the choice of the design that strives to optimize several variances simultaneously. Incorporating the contemporaneous means and their variances tends to shift the preferences from observation-panel towards simpler panel-cluster and independent designs if the panel mode of data collection is too expensive. We present numeric illustrations demonstrating how a survey designer may want to choose the efficient design given the population parameters and data collection cost.
Release date: 2011-06-29
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Analysis (9)
Analysis (9) ((9 results))
- Articles and reports: 12-001-X201100211606Description:
This paper introduces a U.S. Census Bureau special compilation by presenting four other papers of the current issue: three papers from authors Tillé, Lohr and Thompson as well as a discussion paper from Opsomer.
Release date: 2011-12-21 - 2. Adaptive network and spatial sampling ArchivedArticles and reports: 12-001-X201100211607Description:
This paper describes recent developments in adaptive sampling strategies and introduces new variations on those strategies. Recent developments described included targeted random walk designs and adaptive web sampling. These designs are particularly suited for sampling in networks; for example, for finding a sample of people from a hidden human population by following social links from sample individuals to find additional members of the hidden population to add to the sample. Each of these designs can also be translated into spatial settings to produce flexible new spatial adaptive strategies for sampling unevenly distributed populations. Variations on these sampling strategies include versions in which the network or spatial links have unequal weights and are followed with unequal probabilities.
Release date: 2011-12-21 - Articles and reports: 12-001-X201100211608Description:
Designs and estimators for the single frame surveys currently used by U.S. government agencies were developed in response to practical problems. Federal household surveys now face challenges of decreasing response rates and frame coverage, higher data collection costs, and increasing demand for small area statistics. Multiple frame surveys, in which independent samples are drawn from separate frames, can be used to help meet some of these challenges. Examples include combining a list frame with an area frame or using two frames to sample landline telephone households and cellular telephone households. We review point estimators and weight adjustments that can be used to analyze multiple frame surveys with standard survey software, and summarize construction of replicate weights for variance estimation. Because of their increased complexity, multiple frame surveys face some challenges not found in single frame surveys. We investigate misclassification bias in multiple frame surveys, and propose a method for correcting for this bias when misclassification probabilities are known. Finally, we discuss research that is needed on nonsampling errors with multiple frame surveys.
Release date: 2011-12-21 - Articles and reports: 12-001-X201100211609Description:
This paper presents a review and assessment of the use of balanced sampling by means of the cube method. After defining the notion of balanced sample and balanced sampling, a short history of the concept of balancing is presented. The theory of the cube method is briefly presented. Emphasis is placed on the practical problems posed by balanced sampling: the interest of the method with respect to other sampling methods and calibration, the field of application, the accuracy of balancing, the choice of auxiliary variables and ways to implement the method.
Release date: 2011-12-21 - 5. Innovations in survey sampling design: Discussion of three contributions presented at the U.S. Census Bureau ArchivedArticles and reports: 12-001-X201100211610Description:
In this paper, a discussion of the three papers from the US Census Bureau special compilation is presented.
Release date: 2011-12-21 - Articles and reports: 89-648-X2011001Geography: CanadaDescription:
In January 2006, a conference on longitudinal surveys hosted by Statistics Canada, the Social and Humanities Research Council of Canada (SSHRC) and the Canadian Institute of Health Research (CIHR) concluded that Canada lacks a longitudinal survey which collects information on multiple subjects such as family, human capital, labour health and follows respondents for a long period of time. Following this conference, funds were received from the Policy Research Data Gaps fund (PRDG) to support a pilot survey for a new Canadian Household Panel Survey (CHPS-Pilot). Consultations on the design and content were held with academic and policy experts in 2007 and 2008, and a pilot survey was conducted in the fall of 2008. The objectives of the pilot survey were to (1) test a questionnaire, evaluate interview length and measure the quality of data collected, (2) evaluate several design features; and (3) test reactions to the survey from respondents and field workers. The pilot survey achieved a response rate of 76%, with a median household interview time of 64 minutes. Several innovative design features were tested, and found to be viable. Response to the survey, whether from respondents or interviewers, was generally positive. This paper highlights these and other results from the CHPS-Pilot.
Release date: 2011-09-14 - Articles and reports: 12-001-X201100111447Description:
This paper introduces a R-package for the stratification of a survey population using a univariate stratification variable X and for the calculation of stratum sample sizes. Non iterative methods such as the cumulative root frequency method and the geometric stratum boundaries are implemented. Optimal designs, with stratum boundaries that minimize either the CV of the simple expansion estimator for a fixed sample size n or the n value for a fixed CV can be constructed. Two iterative algorithms are available to find the optimal stratum boundaries. The design can feature a user defined certainty stratum where all the units are sampled. Take-all and take-none strata can be included in the stratified design as they might lead to smaller sample sizes. The sample size calculations are based on the anticipated moments of the survey variable Y, given the stratification variable X. The package handles conditional distributions of Y given X that are either a heteroscedastic linear model, or a log-linear model. Stratum specific non-response can be accounted for in the design construction and in the sample size calculations.
Release date: 2011-06-29 - Articles and reports: 12-001-X201100111448Description:
In two-phase sampling for stratification, the second-phase sample is selected by a stratified sample based on the information observed in the first-phase sample. We develop a replication-based bias adjusted variance estimator that extends the method of Kim, Navarro and Fuller (2006). The proposed method is also applicable when the first-phase sampling rate is not negligible and when second-phase sample selection is unequal probability Poisson sampling within each stratum. The proposed method can be extended to variance estimation for two-phase regression estimators. Results from a limited simulation study are presented.
Release date: 2011-06-29 - 9. Cost efficiency of repeated cluster surveys ArchivedArticles and reports: 12-001-X201100111449Description:
We analyze the statistical and economic efficiency of different designs of cluster surveys collected in two consecutive time periods, or waves. In an independent design, two cluster samples in two waves are taken independently from one another. In a cluster-panel design, the same clusters are used in both waves, but samples within clusters are taken independently in two time periods. In an observation-panel design, both clusters and observations are retained from one wave of data collection to another. By assuming a simple population structure, we derive design variances and costs of the surveys conducted according to these designs. We first consider a situation in which the interest lies in estimation of the change in the population mean between two time periods, and derive the optimal sample allocations for the three designs of interest. We then propose the utility maximization framework borrowed from microeconomics to illustrate a possible approach to the choice of the design that strives to optimize several variances simultaneously. Incorporating the contemporaneous means and their variances tends to shift the preferences from observation-panel towards simpler panel-cluster and independent designs if the panel mode of data collection is too expensive. We present numeric illustrations demonstrating how a survey designer may want to choose the efficient design given the population parameters and data collection cost.
Release date: 2011-06-29
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