Social surveys are usually affected by item and unit nonresponse. Since it is unlikely that a sample of respondents is a random sample, social scientists should take the missing data problem into account in their empirical analyses. Typically, survey methodologists try to simplify the work of data users by "completing'" the data, filling the missing variables through imputation. The aim of this paper is to give data users some guidelines on how to assess the effects of imputation on their micro-level analyses. We focus attention on the potential bias caused by imputation in the analysis of income variables and poverty measures. We consider two methods for evaluating the effects of imputation, using the European Community Household Panel as an illustration.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Publisher Info
Paper provided by Institute for Social and Economic Research in its series ISER working papers with number
2004-19.
Length: 0 Date of creation: 01 Oct 2004 Date of revision: Publication status: published Handle: RePEc:ese:iserwp:2004-19
Contact details of provider: Postal: Publications Office, Institute for Social and Economic Research, University of Essex, Wivenhoe Park, Colchester, Essex CO4 3SQ UK Phone: 44-1206-872957 Fax: 44-1206-873151 Web page: http://www.iser.essex.ac.uk/
Order Information: Postal: Publications Office, Institute for Social and Economic Research, University of Essex, Wivenhoe Park, Colchester, Essex CO4 3SQ UK Email: Web: http://www.iser.essex.ac.uk/publications/
For technical questions regarding this item, or to correct its listing, contact: (Paul Groves).
Related research
Keywords:
This paper has been announced in the following NEP Reports: