Weighting and estimation

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All (4) ((4 results))

  • 1. Sampling with unequal probabilities and without replacement - A rejective method Archived
    Articles and reports: 12-001-X197900254834
    Description: An alternative to the direct selection of sample is suggested, which while retaining the efficiency at the same level simplifies the selection and variance estimation processes in a wide variety of situations. If n* is the largest feasible pPS sample size that can be drawn from a given population of size N, then the proposed method entails selection of m (=N - n*) units using a pPS scheme and rejecting these units from the population such that the remainder is a pPS sample of n* units; the final sample of n units is then selected as a subsample from the remainder set. This method for selecting the pPS sample can be seen as an analogue of SRS where it is well known that the “unsampled” part of the population as well as any subsample from this part are also SRS from the entire population when SRS is the procedure used. The method is very practical for situations where m is less than the actual sample size n. Moreover, the method has the additional advantage in the context of continuing surveys, e.g. Canadian Labour Force Survey (LFS), where the number of primary sampling units (PSU’s) may have to be increased (or decreased) subsequent to the initial selection of the sample. The method also has advantages in the case of sample rotation. Main features of the proposed scheme and its limitations are given. Efficiency of the method is also evaluated empirically.
    Release date: 1979-12-15
  • 2. An empirical investigation of an improved method of measuring correlated response variance Archived
    Articles and reports: 12-001-X197900100003
    Description: Two methods for estimating the correlated response variance of a survey estimator are studied by way of both theoretical comparison and empirical investigation. The variance of these estimators is discussed and the effects of outliers examined. Finally, an improved estimator is developed and evaluated.
    Release date: 1979-06-15
  • 3. On the inclusion of large units in simple random sampling Archived
    Articles and reports: 12-001-X197900100005
    Description: Approximate cutoff rules for stratifying a population into a take-all and take-some universe have been given by Dalenius (1950) and Glasser (1962). They expressed the cutoff value (that value which delineates the boundary of the take-all and take-some) as a function of the mean, the sampling weight and the population variance. Their cutoff values were derived on the assumption that a single random sample of size n was to be drawn without replacement from the population of size N.

    In the present context, exact and approximate cutoff rules have been worked out for a similar situation. Rather than providing the sample size of the sample, the precision (coefficient of variation) is given. Note that in many sampling situations, the sampler is given a set of objectives in terms of reliability and not sample size. The result is particularly useful for determining the take-all - take-some boundary for samples drawn from a known population. The procedure is also extended to ratio estimation.
    Release date: 1979-06-15
  • 4. Unbiased estimation of proportions under sequential sampling Archived
    Articles and reports: 12-001-X197900100006
    Description: Under a sequential sampling plan, the proportion defective in the sample is generally a biased estimator of the population value. In this paper, an unbiased estimator is given. Also, an unbiased estimator of its variance is derived. These results are applied to an estimation problem from the 1976 Canadian Census.
    Release date: 1979-06-15
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Analysis (4)

Analysis (4) ((4 results))

  • 1. Sampling with unequal probabilities and without replacement - A rejective method Archived
    Articles and reports: 12-001-X197900254834
    Description: An alternative to the direct selection of sample is suggested, which while retaining the efficiency at the same level simplifies the selection and variance estimation processes in a wide variety of situations. If n* is the largest feasible pPS sample size that can be drawn from a given population of size N, then the proposed method entails selection of m (=N - n*) units using a pPS scheme and rejecting these units from the population such that the remainder is a pPS sample of n* units; the final sample of n units is then selected as a subsample from the remainder set. This method for selecting the pPS sample can be seen as an analogue of SRS where it is well known that the “unsampled” part of the population as well as any subsample from this part are also SRS from the entire population when SRS is the procedure used. The method is very practical for situations where m is less than the actual sample size n. Moreover, the method has the additional advantage in the context of continuing surveys, e.g. Canadian Labour Force Survey (LFS), where the number of primary sampling units (PSU’s) may have to be increased (or decreased) subsequent to the initial selection of the sample. The method also has advantages in the case of sample rotation. Main features of the proposed scheme and its limitations are given. Efficiency of the method is also evaluated empirically.
    Release date: 1979-12-15
  • 2. An empirical investigation of an improved method of measuring correlated response variance Archived
    Articles and reports: 12-001-X197900100003
    Description: Two methods for estimating the correlated response variance of a survey estimator are studied by way of both theoretical comparison and empirical investigation. The variance of these estimators is discussed and the effects of outliers examined. Finally, an improved estimator is developed and evaluated.
    Release date: 1979-06-15
  • 3. On the inclusion of large units in simple random sampling Archived
    Articles and reports: 12-001-X197900100005
    Description: Approximate cutoff rules for stratifying a population into a take-all and take-some universe have been given by Dalenius (1950) and Glasser (1962). They expressed the cutoff value (that value which delineates the boundary of the take-all and take-some) as a function of the mean, the sampling weight and the population variance. Their cutoff values were derived on the assumption that a single random sample of size n was to be drawn without replacement from the population of size N.

    In the present context, exact and approximate cutoff rules have been worked out for a similar situation. Rather than providing the sample size of the sample, the precision (coefficient of variation) is given. Note that in many sampling situations, the sampler is given a set of objectives in terms of reliability and not sample size. The result is particularly useful for determining the take-all - take-some boundary for samples drawn from a known population. The procedure is also extended to ratio estimation.
    Release date: 1979-06-15
  • 4. Unbiased estimation of proportions under sequential sampling Archived
    Articles and reports: 12-001-X197900100006
    Description: Under a sequential sampling plan, the proportion defective in the sample is generally a biased estimator of the population value. In this paper, an unbiased estimator is given. Also, an unbiased estimator of its variance is derived. These results are applied to an estimation problem from the 1976 Canadian Census.
    Release date: 1979-06-15
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