The IMPUTE MISSING DATA menu item is available to you when there are missing values in your data. Since data with missing values cannot be used in ViSta's analysis methods, some way of pre-processing the data must be provided. The menu item provides three of the most common methods used to deal with missing data:
1) Listwise deletion: Any observation with a missing value is deleted from the dataset.
2) Pairwise deletion: Correlation/covariance matrices are computed on the basis of cases which do not have pairs of missing values.
3) Maximum Likelihood: An iterative process attempts to obtain maximum likelihood estimates of the missing values. These estimates are used to replace the missing values so that no data has to be thrown out.
