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• 1. Sampling from imperfect frames with unknown amount of duplication Archived

  Articles and reports: 12-001-X199300214454

  Description:

  This study covers such imperfect frames in which no population unit has been excluded from the frame but an unspecified number of population units may have been included in the list an unspecified number of times each with a separate identification. When the availability of auxiliary information on any unit in the imperfect frame is not assumed, it is established that for estimation of a population ratio or a mean, the mean square errors of estimators based on the imperfect frame are less than those based on the perfect frame for simple random sampling when the sampling fractions of perfect and imperfect frames are the same. For estimation of a population total, however, this is not always true. Also, there are situations in which estimators of a ratio, a mean or a total based on smaller sampling fraction from imperfect frame can have smaller mean square error than those based on a larger sampling fraction from the perfect frame.

  Release date: 1993-12-15

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• 2. Forgot the sampling scheme at the estimation stage? Archived

  Articles and reports: 12-001-X199000214530

  Description:

  For a class of linear unbiased estimators in a class of sampling schemes, it is shown that one can forget the weights used for sample selection while estimating a population ratio by a ratio of two unbiased estimators, respectively of the numerator and the denominator defining the population ratio. This class of schemes includes commonly used sampling schemes such as unequal probability sampling with or without replacement, stratified proportional allocation sampling with unequal selection probabilities and without replacement in each stratum, etc.

  Release date: 1990-12-14

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Articles and reports (2) ((2 results))

• 1. Sampling from imperfect frames with unknown amount of duplication Archived

  Articles and reports: 12-001-X199300214454

  Description:

  This study covers such imperfect frames in which no population unit has been excluded from the frame but an unspecified number of population units may have been included in the list an unspecified number of times each with a separate identification. When the availability of auxiliary information on any unit in the imperfect frame is not assumed, it is established that for estimation of a population ratio or a mean, the mean square errors of estimators based on the imperfect frame are less than those based on the perfect frame for simple random sampling when the sampling fractions of perfect and imperfect frames are the same. For estimation of a population total, however, this is not always true. Also, there are situations in which estimators of a ratio, a mean or a total based on smaller sampling fraction from imperfect frame can have smaller mean square error than those based on a larger sampling fraction from the perfect frame.

  Release date: 1993-12-15

  ---

• 2. Forgot the sampling scheme at the estimation stage? Archived

  Articles and reports: 12-001-X199000214530

  Description:

  For a class of linear unbiased estimators in a class of sampling schemes, it is shown that one can forget the weights used for sample selection while estimating a population ratio by a ratio of two unbiased estimators, respectively of the numerator and the denominator defining the population ratio. This class of schemes includes commonly used sampling schemes such as unequal probability sampling with or without replacement, stratified proportional allocation sampling with unequal selection probabilities and without replacement in each stratum, etc.

  Release date: 1990-12-14

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