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F. Kreuter (2009)
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International Journal of Public Opinion Research Vol. 23 No. 3 The Author 2011 . Published by Oxford University Press on behalf of The World Association for Public Opinion Research. All rights reserved. doi:10 .1093 /ijpor/edr503 The Report of the International Workshop on Using Multi-level Data from Sample Frames, Auxiliary Databases, Paradata and Related Sources to Detect and Adjust for Nonresponse Bias in Surveys* Tom W. Smith NORC/University of Chicago, Chicago, Illinois, USA This workshop report considers (a) how auxiliary data (AD) can be used to analyze nonresponse bias, (b) other benefits of using AD, (c) recommendations regarding using AD for nonresponse analysis relating to (i) sample frames, (ii) linked databases, (iii) paradata, (iv) aggregate data, and (v) AD in general, (d) propensity models, (e) resources for nonresponse analysis, and (f) nonresponse bias measures. Using AD to Detect and Adjust for Nonresponse Nonresponse is appreciable in most general-population surveys and has been increasing over time (de Leeuw & de Heer, 2002 ; Couper & de Leeuw, 2003 ; Kreuter, forthcoming; Stoop et al., 2010 a). Nonresponse usually does not lead to data that are missing at random and thus it is not ignorable. So surveys need to take steps to
International Journal of Public Opinion Research – Oxford University Press
Published: Sep 24, 2011
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