Output (Multiple Imputation)

Display. Controls display of output. An overall imputation summary is always displayed, which includes tables relating the imputation specifications, iterations (for fully conditional specification method), dependent variables imputed, dependent variables excluded from imputation, and imputation sequence. If specified, constaints for analysis variables are also shown.

  • Imputation model. This displays the imputation model for dependent variables and predictors, and includes univariate model type, model effects, and number of values imputed.
  • Descriptive statistics. This displays descriptive statistics for dependent variables for which values are imputed. For scale variables the descriptive statistics include mean, count, standard deviation, min, and max for the original input data (prior to imputation), imputed values (by imputation), and complete data (original and imputed values together—by imputation). For categorical variables the descriptive statistics include count and percent by category for the original input data (prior to imputation), imputed values (by imputation), and complete data (original and imputed values together—by imputation).

Iteration History. When the fully conditional specification imputation method is used, you can request a dataset that contains iteration history data for FCS imputation. The dataset contains means and standard deviations by iteration and imputation for each scale dependent varable for which values are imputed. You can plot the data to help assess model convergence.

How To Select Output for Multiple Imputation

This feature requires the Missing Values option.

  1. From the menus choose:

    Analyze > Multiple Imputation > Impute Missing Data Values...

  2. In the Impute Missing Data Values dialog box, click the Output tab.