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Repräsentativität von Subgruppen bei geschichteten Zufallsstichproben

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  • Siegfried Gabler
  • Andreas Quatember

Abstract

The concept of a representative sample can be found in nearly every survey description. In general, this means that the sample is a miniature of the population. A scientific definition of the term should include all important aspects of a sample survey. In this paper such a definition is discussed. Besides the theoretical aspects of the sample design such as the sampling method and the estimation technique, it comprises practical aspects occurring also in population surveys such as nonresponse and untruthful answering. Given this sample design, the chosen sample number determines the survey’s sampling error. The question of the necessary sample number for a certain efficiency of the estimator is discussed. Based on that, the question on the sample numbers in subgroups of a stratified random sample, relevant in practice, is considered. These sample numbers have to allow for representativeness in each subgroup. The solution of this problem can be described by a convex minimization program under box constraints and linear inequality constraints. A numerical example illustrates the proposed procedure. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Siegfried Gabler & Andreas Quatember, 2013. "Repräsentativität von Subgruppen bei geschichteten Zufallsstichproben," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 7(3), pages 105-119, December.
  • Handle: RePEc:spr:astaws:v:7:y:2013:i:3:p:105-119
    DOI: 10.1007/s11943-013-0132-3
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    References listed on IDEAS

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    1. Roberto Benedetti & Giuseppe Espa & Giovanni Lafratta, 2005. "A tree-based approach to forming strata in multipurpose business surveys," Department of Economics Working Papers 0505, Department of Economics, University of Trento, Italia.
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    Cited by:

    1. Heinrichs, Heidi Ursula & Schumann, Diana & Vögele, Stefan & Biß, Klaus Hendrik & Shamon, Hawal & Markewitz, Peter & Többen, Johannes & Gillessen, Bastian & Gotzens, Fabian & Ernst, Anna, 2017. "Integrated assessment of a phase-out of coal-fired power plants in Germany," Energy, Elsevier, vol. 126(C), pages 285-305.
    2. Beate Jahn & Sarah Friedrich & Joachim Behnke & Joachim Engel & Ursula Garczarek & Ralf Münnich & Markus Pauly & Adalbert Wilhelm & Olaf Wolkenhauer & Markus Zwick & Uwe Siebert & Tim Friede, 2022. "On the role of data, statistics and decisions in a pandemic," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(3), pages 349-382, September.

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      More about this item

      Keywords

      Stichprobenerhebung; Schwankungsbreite; Designeffekt; konvexe Minimierung; C83; Sample Survey; Band width; Design effect; Convex minimization;
      All these keywords.

      JEL classification:

      • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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