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Mathematical Background

  • Verena Puchner
Chapter
Part of the BestMasters book series (BEST)

Abstract

To explain some methods for combining two data sets consider the following situation: Let A and B be two sample surveys. The number of observations are different and not all variables in the two data sets are the same. Moreover some of the variables are observed in both surveys, some are observed in the sample survey A und some other variables are only available in the sample survey B. The idea is now to estimate the missing variables in one survey, lets say in A. Assume that this variable of interest has been observed in the survey B. Many different possibilities to perform this estimation exists. In this chapter the following kind of methods are considered:
  1. 1.

    Regression Models including selected unit-level Small Area Methods

     
  2. 2.

    Statistical Matching

     

Keywords

Ordinary Little Square Model Matrix Bootstrap Sample Breakdown Point Matching Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Fachmedien Wiesbaden 2015

Authors and Affiliations

  1. 1.Tieto Austria GmbHViennaAustria

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