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- Articles and reports: 12-001-X202200200011Description:
Two-phase sampling is a cost effective sampling design employed extensively in surveys. In this paper a method of most efficient linear estimation of totals in two-phase sampling is proposed, which exploits optimally auxiliary survey information. First, a best linear unbiased estimator (BLUE) of any total is formally derived in analytic form, and shown to be also a calibration estimator. Then, a proper reformulation of such a BLUE and estimation of its unknown coefficients leads to the construction of an “optimal” regression estimator, which can also be obtained through a suitable calibration procedure. A distinctive feature of such calibration is the alignment of estimates from the two phases in an one-step procedure involving the combined first-and-second phase samples. Optimal estimation is feasible for certain two-phase designs that are used often in large scale surveys. For general two-phase designs, an alternative calibration procedure gives a generalized regression estimator as an approximate optimal estimator. The proposed general approach to optimal estimation leads to the most effective use of the available auxiliary information in any two-phase survey. The advantages of this approach over existing methods of estimation in two-phase sampling are shown both theoretically and through a simulation study.
Release date: 2022-12-15 - Articles and reports: 12-001-X201500114174Description:
Matrix sampling, often referred to as split-questionnaire, is a sampling design that involves dividing a questionnaire into subsets of questions, possibly overlapping, and then administering each subset to one or more different random subsamples of an initial sample. This increasingly appealing design addresses concerns related to data collection costs, respondent burden and data quality, but reduces the number of sample units that are asked each question. A broadened concept of matrix design includes the integration of samples from separate surveys for the benefit of streamlined survey operations and consistency of outputs. For matrix survey sampling with overlapping subsets of questions, we propose an efficient estimation method that exploits correlations among items surveyed in the various subsamples in order to improve the precision of the survey estimates. The proposed method, based on the principle of best linear unbiased estimation, generates composite optimal regression estimators of population totals using a suitable calibration scheme for the sampling weights of the full sample. A variant of this calibration scheme, of more general use, produces composite generalized regression estimators that are also computationally very efficient.
Release date: 2015-06-29 - Articles and reports: 12-001-X20010026093Description:
This paper presents weighting procedures that combine information from multiple panels of a repeated panel household survey for cross-sectional estimation. The dynamic character of a repeated panel survey is discussed in relation to estimation of population parameters at any wave of the survey. A repeated panel survey with overlapping panels is described as a special type of multiple frame survey, with the frames of the panels forming a time sequence. The paper proposes weighting strategies suitable for various multiple panel survey situations. The proposed weighting schemes involve an adjustment of weights in domains of the combined panel sample that represent identical time periods covered by the individual panels. A weight adjustment procedure that deals with changes in the panels over time is discussed. The integration of the various weight adjustments required for cross-sectional estimation in a repeated panel household survey is also discussed.
Release date: 2002-02-28 - Articles and reports: 75F0002M2000006Description:
This paper discusses methods and tools considered and used to produce cross-sectional estimates based on the combination of two longitudinal panels for the Survey of Labour and Income Dynamics (SLID).
Release date: 2000-10-05
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Articles and reports (4)
Articles and reports (4) ((4 results))
- Articles and reports: 12-001-X202200200011Description:
Two-phase sampling is a cost effective sampling design employed extensively in surveys. In this paper a method of most efficient linear estimation of totals in two-phase sampling is proposed, which exploits optimally auxiliary survey information. First, a best linear unbiased estimator (BLUE) of any total is formally derived in analytic form, and shown to be also a calibration estimator. Then, a proper reformulation of such a BLUE and estimation of its unknown coefficients leads to the construction of an “optimal” regression estimator, which can also be obtained through a suitable calibration procedure. A distinctive feature of such calibration is the alignment of estimates from the two phases in an one-step procedure involving the combined first-and-second phase samples. Optimal estimation is feasible for certain two-phase designs that are used often in large scale surveys. For general two-phase designs, an alternative calibration procedure gives a generalized regression estimator as an approximate optimal estimator. The proposed general approach to optimal estimation leads to the most effective use of the available auxiliary information in any two-phase survey. The advantages of this approach over existing methods of estimation in two-phase sampling are shown both theoretically and through a simulation study.
Release date: 2022-12-15 - Articles and reports: 12-001-X201500114174Description:
Matrix sampling, often referred to as split-questionnaire, is a sampling design that involves dividing a questionnaire into subsets of questions, possibly overlapping, and then administering each subset to one or more different random subsamples of an initial sample. This increasingly appealing design addresses concerns related to data collection costs, respondent burden and data quality, but reduces the number of sample units that are asked each question. A broadened concept of matrix design includes the integration of samples from separate surveys for the benefit of streamlined survey operations and consistency of outputs. For matrix survey sampling with overlapping subsets of questions, we propose an efficient estimation method that exploits correlations among items surveyed in the various subsamples in order to improve the precision of the survey estimates. The proposed method, based on the principle of best linear unbiased estimation, generates composite optimal regression estimators of population totals using a suitable calibration scheme for the sampling weights of the full sample. A variant of this calibration scheme, of more general use, produces composite generalized regression estimators that are also computationally very efficient.
Release date: 2015-06-29 - Articles and reports: 12-001-X20010026093Description:
This paper presents weighting procedures that combine information from multiple panels of a repeated panel household survey for cross-sectional estimation. The dynamic character of a repeated panel survey is discussed in relation to estimation of population parameters at any wave of the survey. A repeated panel survey with overlapping panels is described as a special type of multiple frame survey, with the frames of the panels forming a time sequence. The paper proposes weighting strategies suitable for various multiple panel survey situations. The proposed weighting schemes involve an adjustment of weights in domains of the combined panel sample that represent identical time periods covered by the individual panels. A weight adjustment procedure that deals with changes in the panels over time is discussed. The integration of the various weight adjustments required for cross-sectional estimation in a repeated panel household survey is also discussed.
Release date: 2002-02-28 - Articles and reports: 75F0002M2000006Description:
This paper discusses methods and tools considered and used to produce cross-sectional estimates based on the combination of two longitudinal panels for the Survey of Labour and Income Dynamics (SLID).
Release date: 2000-10-05
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