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Web Survey Bibliography

Title Missing data
Author de Leeuw, E. D., Hox, J.
Year 2008
Access date 05.05.2013

An important indicator of data quality is the fraction of missing data. Missing data (also called "item non-response") means that for some reason data on particular items or questions are not available for analysis. In practice, many researchers tend to solve this problem by restricting the analysis to complete cases through "listwise" deletion of all cases with missing data on the variables of interest. However, this results in loss of information, and therefore estimates will be less efficient. Furthermore, there is the possibility of systematic differences between units that respond to a particular question and those that do not respond—that is, item nonresponse error. If this is the case, the basic assumptions necessary for analyzing only complete cases are not met, and the analysis results may be severely biased. Modern strategies to cope with missing data are imputation and direct estimation . Imputation replaces the missing values with plausible estimates ...

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Year of publication2008
Bibliographic typeBook section
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