Missing data problems, including nonresponse problems, are troublesome because the sampling probabilities are unknown, and cannot be determined even with large samples. Judgment must be used in the analysis and should be reflected in expressions of uncertainty. During the design of a study, many choices must be made between collecting more observations or devoting resources to reducing nonresponse or estimating its effects. Mean square error appears to be a more useful concept in making these tradeoffs than unbiasedness. Dual data collection systems are helpful for measuring nonresponse.
This report is part of the RAND Corporation Note series. The note was a product of the RAND Corporation from 1979 to 1993 that reported other outputs of sponsored research for general distribution.
Permission is given to duplicate this electronic document for personal use only, as long as it is unaltered and complete. Copies may not be duplicated for commercial purposes. Unauthorized posting of RAND PDFs to a non-RAND Web site is prohibited. RAND PDFs are protected under copyright law. For information on reprint and linking permissions, please visit the RAND Permissions page.
The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.