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Digest of Education Statistics: 2011
Digest of Education Statistics: 2011

NCES 2012-001
May 2012

Appendix A.1. Nonsampling Errors

Universe and sample surveys are subject to nonsampling errors. Nonsampling errors may arise when respondents or interviewers interpret questions differently; when respondents must estimate values, or when coders, keyers, and other processors handle answers differently; when people who should be included in the universe are not; or when people fail to respond (completely or partially). Nonsampling errors usually, but not always, result in an underestimate of total survey error and thus an overestimate of the precision of survey estimates. Since estimating the magnitude of nonsampling errors often would require special experiments or access to independent data, these nonsampling errors are seldom measured.

To compensate for nonresponse, adjustments of the sample estimates are often made. For universe surveys, an adjustment made for either type of nonresponse, total or partial, is often referred to as an imputation, which is often a substitution of the "average" questionnaire response for the nonresponse. For universe surveys, imputations are usually made separately within various groups of sample members that have similar survey characteristics. For sample surveys, missing cases (i.e., total nonresponse) are handled through nonresponse adjustments to the sample weights. For sample surveys, imputation for item nonresponse is usually made by substituting for a missing item the response to that item of a respondent having characteristics that are similar to those of the nonrespondent. For more information, see the NCES Statistical Standards (NCES 2003-601).

Although the magnitude of nonsampling error in the data compiled in this Digest is frequently unknown, idiosyncrasies that have been identified are noted in the appropriate tables.