Abstract
Missing data are a ubiquitous problem in quantitative communication research, yet the missing data handling practices found in most published work in communication leave much room for improvement. In this article, problems with current practices are discussed and suggestions for improvement are offered. Finally, hot deck imputation is suggested as a practical solution to many missing data problems. A computational tool for SPSS (Statistical Package for the Social Sciences) is presented that will enable communication researchers to easily implement hot deck imputation in their own analyses.
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