Working with Multiple Imputation Data
When a multiple imputation (MI) dataset is created, a variable called Imputation_, with variable label Imputation Number, is added, and the dataset is sorted by it in ascending order. Cases from the original dataset has a value of 0. Cases for imputed values are numbered 1 through M, where M is the number of imputations.
When you open a dataset, the presence of Imputation_ identifies the dataset as a possible MI dataset.
Activating a Multiple Imputation Dataset for Analysis
The dataset must be split using the Compare groups option, with Imputation_ as a grouping variable, in order to be treated as an MI dataset in analyses. See the topic Split file for more information. You can also define splits on other variables.
From the menus choose:
- Select Compare groups.
- Select Imputation Number [Imputation_] as a variable to group cases on.
Alternatively, when you turn markings on (see below), the the file is split on Imputation Number [Imputation_].
Distinguishing Imputed Values from Observed Values
You can distinguish imputed values from observed values by cell background color, the font, and bold type (for imputed values). When you create a new dataset in the current session with Impute Missing Values, markings are turned on by default. When you open a saved data file that includes imputations, markings are turned off.
To turn markings on, from the Data Editor menus choose:
Alternatively, you can turn on markings by clicking the imputation marking button at the right edge of the edit bar in Data View of the Data Editor.
Moving Between Imputations
- From the menus choose:
- Select the imputation (or Original data) from the drop-down list.
Alternatively, you can select the imputation from the drop-down list in the edit bar in Data View of the Data Editor.
Relative case position is preserved when selecting imputations. For example, if there are 1000 cases in the original dataset, case 1034, the 34th case in the first imputation, displays at the top of the grid. If you select imputation 2 in the dropdown, case 2034, the 34th case in imputation 2, would display at the top of the grid. If you select Original data in the dropdown, case 34 would display at the top of the grid. Column position is also preserved when navigating between imputations, so that it is easy to compare values between imputations.
Transforming and Editing Imputed Values
Sometimes you will need to perform transformations on imputed data. For example, you may want to take the log of all values of a salary variable and save the result in a new variable. A value computed using imputed data will be treated as imputed if it differs from the value computed using the original data.
If you edit an imputed value in a cell of the Data Editor, that cell is still treated as imputed. It is not recommended to edit imputed values in this way.