Impute Missing Values

The five columns that have missing values are continuous. You proceed to impute values for the four columns other than Column J using multivariate imputation for the continuous columns in your data table. By doing so, you tacitly assume that the probabilities that values are missing depend only on the values of the continuous variables and not on the values of excluded nominal variables. To conduct this new analysis, you need to launch the Explore Missing Values utility again.

Select Analyze > Screening > Explore Missing Values.

In the launch window, click the red triangle next to 280 Columns.

You will use the columns filter menu to view only the columns with a Continuous modeling type in the Select Columns list.

Select Modeling Type > Uncheck All.

This removes all columns from the Select Columns list.

Select Modeling Type > Continuous.

The Select Columns list now contains only the 207 columns that are Continuous.

Select all 207 columns. Then Ctrl-click the J column (to deselect it) and click Y, Columns.

Click OK.

Click Multivariate Normal Imputation.

A window appears and asks whether you want to use a Shrinkage estimator for covariances.

Click Yes Shrinkage.

A JMP Alert appears, informing you that you should use the Save As command to preserve your original data.

Click OK.

Imputation Report

The Imputation Report in Imputation Report indicates how many missing values were imputed and the specific imputation details. No missing data remain in the four columns that had missing values.