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- Articles and reports: 12-001-X19980013910Description:
Let A be a population domain of interest and assume that the elements of A cannot be identified on the sampling frame and the number of elements in A is not known. Further assume that a sample of fixed size (say n) is selected from the entire frame and the resulting domain sample size (say n_A) is random. The problem addressed is the construction of a confidence interval for a domain parameter such as the domain aggregate T_A = \sum_{i \in A} x_i. The usual approach to this problem is to redefine x_i, by setting x_i = 0 if i \notin A. Thus, the construction of a confidence interval for the domain total is recast as the construction of a confidence interval for a population total which can be addressed (at least asymptotically in n) by normal theory. As an alternative, we condition on n_A and construct confidence intervals which have approximately nominal coverage under certain assumptions regarding the domain population. We evaluate the new approach empirically using artificial populations and data from the Bureau of Labor Statistics (BLS) Occupational Compensation Survey.
Release date: 1998-07-31 - Articles and reports: 12-001-X19970023618Description:
Statistical agencies often constitute their business panels by Poisson sampling, or by stratified sampling of fixed size and uniform probabilities in each stratum. This stampling corresponds to algorithms which use permanent numbers following a uniform distribution. Since the characteristics of the units change over time, it is necessary to periodically conduct resamplings while endeavouring to conserve the maximum number of units. The solution by Poisson sampling is the simplest and provides the maximum theoretical coverage, but with the disadvantage of a random sample size. On the other hand, in the case of stratified sampling of fixed size, the changes in strata cause difficulties precisely because of these fixed size constraints. An initial difficulty is that the finer the stratification, the more the coverage is decreased. Indeed, this is likely to occur if births constitute separate strata. We show how this effect can be corrected by rendering the numbers equidistant before resampling. The disadvantage, a fairly minor one, is that in each stratum the sampling is no longer a simple random sampling, which makes the estimation of the variance less rigorous. Another difficulty is reconciling the resampling with an eventual rotation of the units in the sample. We present a type of algorithm which extends after resampling the rotation before resampling. It is based on transformations of the random numbers used for the sampling, so as to return to resampling without rotation. These transformations are particularly simple when they involve equidistant numbers, but can also be carried out with the numbers following a uniform distribution.
Release date: 1998-03-12 - Articles and reports: 61-532-X19970013496Description:
Society is changing, its information needs are multiplying, and as a result, the National Systems of Information take advantage of the technology available and adjust their mechanisms and ways of generating statistical and geographical data so as to provide new products and services to effectively to meet these new requirements.
Release date: 1998-02-02
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Articles and reports (3)
Articles and reports (3) ((3 results))
- Articles and reports: 12-001-X19980013910Description:
Let A be a population domain of interest and assume that the elements of A cannot be identified on the sampling frame and the number of elements in A is not known. Further assume that a sample of fixed size (say n) is selected from the entire frame and the resulting domain sample size (say n_A) is random. The problem addressed is the construction of a confidence interval for a domain parameter such as the domain aggregate T_A = \sum_{i \in A} x_i. The usual approach to this problem is to redefine x_i, by setting x_i = 0 if i \notin A. Thus, the construction of a confidence interval for the domain total is recast as the construction of a confidence interval for a population total which can be addressed (at least asymptotically in n) by normal theory. As an alternative, we condition on n_A and construct confidence intervals which have approximately nominal coverage under certain assumptions regarding the domain population. We evaluate the new approach empirically using artificial populations and data from the Bureau of Labor Statistics (BLS) Occupational Compensation Survey.
Release date: 1998-07-31 - Articles and reports: 12-001-X19970023618Description:
Statistical agencies often constitute their business panels by Poisson sampling, or by stratified sampling of fixed size and uniform probabilities in each stratum. This stampling corresponds to algorithms which use permanent numbers following a uniform distribution. Since the characteristics of the units change over time, it is necessary to periodically conduct resamplings while endeavouring to conserve the maximum number of units. The solution by Poisson sampling is the simplest and provides the maximum theoretical coverage, but with the disadvantage of a random sample size. On the other hand, in the case of stratified sampling of fixed size, the changes in strata cause difficulties precisely because of these fixed size constraints. An initial difficulty is that the finer the stratification, the more the coverage is decreased. Indeed, this is likely to occur if births constitute separate strata. We show how this effect can be corrected by rendering the numbers equidistant before resampling. The disadvantage, a fairly minor one, is that in each stratum the sampling is no longer a simple random sampling, which makes the estimation of the variance less rigorous. Another difficulty is reconciling the resampling with an eventual rotation of the units in the sample. We present a type of algorithm which extends after resampling the rotation before resampling. It is based on transformations of the random numbers used for the sampling, so as to return to resampling without rotation. These transformations are particularly simple when they involve equidistant numbers, but can also be carried out with the numbers following a uniform distribution.
Release date: 1998-03-12 - Articles and reports: 61-532-X19970013496Description:
Society is changing, its information needs are multiplying, and as a result, the National Systems of Information take advantage of the technology available and adjust their mechanisms and ways of generating statistical and geographical data so as to provide new products and services to effectively to meet these new requirements.
Release date: 1998-02-02
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