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  • 1. Treatments for link nonresponse in indirect sampling Archived
    Articles and reports: 12-001-X200900211038
    Description:

    We examine overcoming the overestimation in using generalized weight share method (GWSM) caused by link nonresponse in indirect sampling. A few adjustment methods incorporating link nonresponse in using GWSM have been constructed for situations both with and without the availability of auxiliary variables. A simulation study on a longitudinal survey is presented using some of the adjustment methods we recommend. The simulation results show that these adjusted GWSMs perform well in reducing both estimation bias and variance. The advancement in bias reduction is significant.

    Release date: 2009-12-23
  • 2. Comparisons of collection follow-up score functions Archived
    Articles and reports: 11-522-X200800010959
    Description:

    The Unified Enterprise Survey (UES) at Statistics Canada is an annual business survey that unifies more than 60 surveys from different industries. Two types of collection follow-up score functions are currently used in the UES data collection. The objective of using a score function is to maximize the economically weighted response rates of the survey in terms of the primary variables of interest, under the constraint of a limited follow-up budget. Since the two types of score functions are based on different methodologies, they could have different impacts on the final estimates.

    This study generally compares the two types of score functions based on the collection data obtained from the two recent years. For comparison purposes, this study applies each score function method to the same data respectively and computes various estimates of the published financial and commodity variables, their deviation from the true pseudo value and their mean square deviation, based on each method. These estimates of deviation and mean square deviation based on each method are then used to measure the impact of each score function on the final estimates of the financial and commodity variables.

    Release date: 2009-12-03
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Articles and reports (2)

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

  • 1. Treatments for link nonresponse in indirect sampling Archived
    Articles and reports: 12-001-X200900211038
    Description:

    We examine overcoming the overestimation in using generalized weight share method (GWSM) caused by link nonresponse in indirect sampling. A few adjustment methods incorporating link nonresponse in using GWSM have been constructed for situations both with and without the availability of auxiliary variables. A simulation study on a longitudinal survey is presented using some of the adjustment methods we recommend. The simulation results show that these adjusted GWSMs perform well in reducing both estimation bias and variance. The advancement in bias reduction is significant.

    Release date: 2009-12-23
  • 2. Comparisons of collection follow-up score functions Archived
    Articles and reports: 11-522-X200800010959
    Description:

    The Unified Enterprise Survey (UES) at Statistics Canada is an annual business survey that unifies more than 60 surveys from different industries. Two types of collection follow-up score functions are currently used in the UES data collection. The objective of using a score function is to maximize the economically weighted response rates of the survey in terms of the primary variables of interest, under the constraint of a limited follow-up budget. Since the two types of score functions are based on different methodologies, they could have different impacts on the final estimates.

    This study generally compares the two types of score functions based on the collection data obtained from the two recent years. For comparison purposes, this study applies each score function method to the same data respectively and computes various estimates of the published financial and commodity variables, their deviation from the true pseudo value and their mean square deviation, based on each method. These estimates of deviation and mean square deviation based on each method are then used to measure the impact of each score function on the final estimates of the financial and commodity variables.

    Release date: 2009-12-03
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