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Income missing values imputation: EVS 1999 and 2008

  • SARRACINO Francesco

Missing data is a very frequent obstacle in many social science studies. The absence of values on one or more variables can signi?cantly affect statistical analyses by reducing their precision and by introducing selection biases. Being unable to account for these aspects may result in severe misrepresentation of the phenomenon under analysis. For this reason several approaches have been proposed to impute missing values. In present work I will adopt multiple imputation to impute income missing data for Luxembourg in the European Values Study data-set of 1999 and 2008.

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Paper provided by LISER in its series LISER Working Paper Series with number 2011-05.

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Length: 28 pages
Date of creation: Jan 2011
Date of revision:
Handle: RePEc:irs:cepswp:2011-05
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