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• 1. Low Income Lines, 2012-2013 Archived

  Articles and reports: 75F0002M2014003

  Description:

  In order to provide a holographic or complete picture of low income, Statistics Canada uses three complementary low income lines: the Low Income Cut-offs (LICOs), the Low Income Measures (LIMs) and the Market Basket Measure (MBM). While the first two lines were developed by Statistics Canada, the MBM is based on concepts developed by Employment and Social Development Canada. Though these measures differ from one another, they give a generally consistent picture of low income status over time. None of these measures is the best. Each contributes its own perspective and its own strengths to the study of low income, so that cumulatively, the three provide a better understanding of the phenomenon of low income as a whole. These measures are not measures of poverty, but strictly measures of low income.

  Release date: 2014-12-10

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• 2. Three controversies in the history of survey sampling Archived

  Articles and reports: 12-001-X201300211883

  Description:

  The history of survey sampling, dating from the writings of A.N. Kiaer, has been remarkably controversial. First Kiaer himself had to struggle to convince his contemporaries that survey sampling itself was a legitimate procedure. He spent several decades in the attempt, and was an old man before survey sampling became a reputable activity. The first person to provide both a theoretical justification of survey sampling (in 1906) and a practical demonstration of its feasibility (in a survey conducted in Reading which was published in 1912) was A.L. Bowley. In 1925, the ISI meeting in Rome adopted a resolution giving acceptance to the use of both randomization and purposive sampling. Bowley used both. However the next two decades saw a steady tendency for randomization to become mandatory. In 1934 Jerzy Neyman used the relatively recent failure of a large purposive survey to ensure that subsequent sample surveys would need to employ random sampling only. He found apt pupils in M.H. Hansen, W.N. Hurwitz and W.G. Madow, who together published a definitive sampling textbook in 1953. This went effectively unchallenged for nearly two decades. In the 1970s, however, R.M. Royall and his coauthors did challenge the use of random sampling inference, and advocated that of model-based sampling instead. That in turn gave rise to the third major controversy within little more than a century. The present author, however, with several others, believes that both design-based and model-based inference have a useful part to play.

  Release date: 2014-01-15

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

• 1. Low Income Lines, 2012-2013 Archived

  Articles and reports: 75F0002M2014003

  Description:

  In order to provide a holographic or complete picture of low income, Statistics Canada uses three complementary low income lines: the Low Income Cut-offs (LICOs), the Low Income Measures (LIMs) and the Market Basket Measure (MBM). While the first two lines were developed by Statistics Canada, the MBM is based on concepts developed by Employment and Social Development Canada. Though these measures differ from one another, they give a generally consistent picture of low income status over time. None of these measures is the best. Each contributes its own perspective and its own strengths to the study of low income, so that cumulatively, the three provide a better understanding of the phenomenon of low income as a whole. These measures are not measures of poverty, but strictly measures of low income.

  Release date: 2014-12-10

  ---

• 2. Three controversies in the history of survey sampling Archived

  Articles and reports: 12-001-X201300211883

  Description:

  The history of survey sampling, dating from the writings of A.N. Kiaer, has been remarkably controversial. First Kiaer himself had to struggle to convince his contemporaries that survey sampling itself was a legitimate procedure. He spent several decades in the attempt, and was an old man before survey sampling became a reputable activity. The first person to provide both a theoretical justification of survey sampling (in 1906) and a practical demonstration of its feasibility (in a survey conducted in Reading which was published in 1912) was A.L. Bowley. In 1925, the ISI meeting in Rome adopted a resolution giving acceptance to the use of both randomization and purposive sampling. Bowley used both. However the next two decades saw a steady tendency for randomization to become mandatory. In 1934 Jerzy Neyman used the relatively recent failure of a large purposive survey to ensure that subsequent sample surveys would need to employ random sampling only. He found apt pupils in M.H. Hansen, W.N. Hurwitz and W.G. Madow, who together published a definitive sampling textbook in 1953. This went effectively unchallenged for nearly two decades. In the 1970s, however, R.M. Royall and his coauthors did challenge the use of random sampling inference, and advocated that of model-based sampling instead. That in turn gave rise to the third major controversy within little more than a century. The present author, however, with several others, believes that both design-based and model-based inference have a useful part to play.

  Release date: 2014-01-15

Journals and periodicals (0) (0 results)

No content available at this time.