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Practical Tools for Designing and Weighting Survey Samples pp 129–161Cite as

Mathematical Programming

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Part of the book series: Statistics for Social and Behavioral Sciences ((SSBS,volume 51))

Abstract

Earlier chapters examined sample size determination and allocation to strata for a single variable. In reality, almost every survey of any size is multipurpose. Data on a number of different variables are collected on each sample unit. Estimates are made of population values for the full population and for various domains or subpopulations. In addition, a variety of types of estimates may be made, including means, totals, quantiles, and model parameters.

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Notes

  1. 1.

    http://www.solver.com/excel-solver.htm.

  2. 2.

    More detailed help is available for this and all other options at www.solver.com/excel2010/solverhelp.htm.

  3. 3.

    http://support.sas.com/documentation/.

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Author information

Authors and Affiliations

  1. University of Michigan, Ann Arbor, MI, USA

    Richard Valliant

  2. RTI International, Washington, DC, USA

    Jill A. Dever

  3. University of Maryland, College Park, MD, USA

    Frauke Kreuter

Authors
  1. Richard Valliant
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  2. Jill A. Dever
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  3. Frauke Kreuter
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© 2013 Springer Science+Business Media New York

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Valliant, R., Dever, J.A., Kreuter, F. (2013). Mathematical Programming. In: Practical Tools for Designing and Weighting Survey Samples. Statistics for Social and Behavioral Sciences, vol 51. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6449-5_5

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