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- 1. 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 - 3. 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: 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 - Articles and reports: 89-642-X2011004Geography: Province or territoryDescription:
Background Notes This demolinguistic portrait of the French-speaking population in British Columbia was undertaken with the financial support of Canadian Heritage's Official Languages Secretariat, Human Resources and Social Development Canada (HRSDC) and Justice Canada. It is the fourth of a series of portraits of official-language minorities in Canada, prepared by Statistics Canada's Language Statistics Section.
Data sources This portrait of the French-speaking population in British Columbia contains information drawn from Canadian censuses from 1951 to 2006 and the Survey on the Vitality of Official-Language Minorities (SVOLM) conducted in 2006 by Statistics Canada.
Census: The census data contained in this report are drawn from the long census questionnaire, completed by 20% of households and including 61 questions of which 7 are language-related.
Survey on the Vitality of Official-Language Minorities (SVOLM): This is a cross-sectional sample survey. Respondents to the (SVOLM) are selected from the sample of persons who completed the long questionnaire in the 2006 Census.
Release date: 2011-06-14
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- 1. 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 - 3. 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: 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 - Articles and reports: 89-642-X2011004Geography: Province or territoryDescription:
Background Notes This demolinguistic portrait of the French-speaking population in British Columbia was undertaken with the financial support of Canadian Heritage's Official Languages Secretariat, Human Resources and Social Development Canada (HRSDC) and Justice Canada. It is the fourth of a series of portraits of official-language minorities in Canada, prepared by Statistics Canada's Language Statistics Section.
Data sources This portrait of the French-speaking population in British Columbia contains information drawn from Canadian censuses from 1951 to 2006 and the Survey on the Vitality of Official-Language Minorities (SVOLM) conducted in 2006 by Statistics Canada.
Census: The census data contained in this report are drawn from the long census questionnaire, completed by 20% of households and including 61 questions of which 7 are language-related.
Survey on the Vitality of Official-Language Minorities (SVOLM): This is a cross-sectional sample survey. Respondents to the (SVOLM) are selected from the sample of persons who completed the long questionnaire in the 2006 Census.
Release date: 2011-06-14
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