A well-known problem in the analysis of test and questionnaire data is that some item scores may be missing. Advanced methods for the imputation of missing data are available, such as multiple imputation under the multivariate normal model and imputation under the saturated logistic model (Schafer, 1997). Accompanying software was made available by, for example, Schafer (1998a, 1998b) and in SOLAS (2001) and S-Plus 6 for Windows (2001). However, these methods and software may be too complicated for a typical psychological researcher, and for the imputation of his or her missing data, he or she depends on the help of a trained statistician. If available, this statistician may not always have enough time or may not be an experienced software user, so the researcher may decide to simply delete all incomplete observations. To help researchers impute scores using simple methods, two SPSS subroutines were written. The aim of these subroutines is that researchers can apply them easily within SPSS and without experienced help.