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- Articles and reports: 12-001-X201000111249Description:
For many designs, there is a nonzero probability of selecting a sample that provides poor estimates for known quantities. Stratified random sampling reduces the set of such possible samples by fixing the sample size within each stratum. However, undesirable samples are still possible with stratification. Rejective sampling removes poor performing samples by only retaining a sample if specified functions of sample estimates are within a tolerance of known values. The resulting samples are often said to be balanced on the function of the variables used in the rejection procedure. We provide modifications to the rejection procedure of Fuller (2009a) that allow more flexibility on the rejection rules. Through simulation, we compare estimation properties of a rejective sampling procedure to those of cube sampling.
Release date: 2010-06-29 - Articles and reports: 75F0002M2010002Description:
This report compares the aggregate income estimates as published by four different statistical programs. The System of National Accounts provides a portrait of economic activity at the macro economic level. The three other programs considered generate data from a micro-economic perspective: two are survey based (Census of Population and Survey of Labour and Income Dynamics) and the third derives all its results from administrative data (Annual Estimates for Census Families and Individuals). A review of the conceptual differences across the sources is followed by a discussion of coverage issues and processing discrepancies that might influence estimates. Aggregate income estimates with adjustments where possible to account for known conceptual differences are compared. Even allowing for statistical variability, some reconciliation issues remain. These are sometimes are explained by the use of different methodologies or data gathering instruments but they sometimes also remain unexplained.
Release date: 2010-04-06
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- Articles and reports: 12-001-X201000111249Description:
For many designs, there is a nonzero probability of selecting a sample that provides poor estimates for known quantities. Stratified random sampling reduces the set of such possible samples by fixing the sample size within each stratum. However, undesirable samples are still possible with stratification. Rejective sampling removes poor performing samples by only retaining a sample if specified functions of sample estimates are within a tolerance of known values. The resulting samples are often said to be balanced on the function of the variables used in the rejection procedure. We provide modifications to the rejection procedure of Fuller (2009a) that allow more flexibility on the rejection rules. Through simulation, we compare estimation properties of a rejective sampling procedure to those of cube sampling.
Release date: 2010-06-29 - Articles and reports: 75F0002M2010002Description:
This report compares the aggregate income estimates as published by four different statistical programs. The System of National Accounts provides a portrait of economic activity at the macro economic level. The three other programs considered generate data from a micro-economic perspective: two are survey based (Census of Population and Survey of Labour and Income Dynamics) and the third derives all its results from administrative data (Annual Estimates for Census Families and Individuals). A review of the conceptual differences across the sources is followed by a discussion of coverage issues and processing discrepancies that might influence estimates. Aggregate income estimates with adjustments where possible to account for known conceptual differences are compared. Even allowing for statistical variability, some reconciliation issues remain. These are sometimes are explained by the use of different methodologies or data gathering instruments but they sometimes also remain unexplained.
Release date: 2010-04-06
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