Does Weighting for Nonresponse Increase the Variance of Survey Means?
AbstractNonresponse weighting is a common method for handling unit nonresponse in surveys and is aimed at reducing nonresponse bias. Because the method can be accompanied by an increase in variance, the efficacy of weighting adjustments is often seen as a bias-variance trade-off. This view is an oversimplification, because weighting can reduce variance as well as bias. The authors provide a detailed analysis of bias and variance in setting weights to estimate a survey mean based on adjustment cells and suggest that the most important feature of variables for inclusion is that they are predictive of survey outcomes. Prediction of the propensity to respond is a secondary, though useful, goal. The authors also evaluate empirical estimates of root mean squared error for assessing when weighting is effective.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. 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.
Bibliographic InfoPaper provided by Mathematica Policy Research in its series Mathematica Policy Research Reports with number 4937.
Date of creation: 30 Dec 2005
Date of revision:
Contact details of provider:
Postal: Mathematica Policy Research P.O. Box 2393 Princeton, NJ 08543-2393 Attn: Communications
Fax: (609) 799-0005
Web page: http://www.mathematica-mpr.com/
More information through EDIRC
analysis of variance; estimation methods; models; nonresponse rate;
Other versions of this item:
- Rod Little & Sonya Vartivarian, 2004. "Does Weighting for Nonresponse Increase the Variance of Survey Means?," The University of Michigan Department of Biostatistics Working Paper Series 1034, Berkeley Electronic Press.
- Roderick J. Little & Sonya Vartivarian, 2005. "Does Weighting for Nonresponse Increase the Variance of Survey Means?," Mathematica Policy Research Reports 4780, Mathematica Policy Research.
- C - Mathematical and Quantitative Methods
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- repec:ese:iserwp:2009-21 is not listed on IDEAS
- Hindsley, Paul & Landry, Craig E. & Gentner, Brad, 2011. "Addressing onsite sampling in recreation site choice models," Journal of Environmental Economics and Management, Elsevier, vol. 62(1), pages 95-110, July.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joanne Pfleiderer) or (Joanne Lustig).
If references are entirely missing, you can add them using this form.