Analytics SPSS SPSS Statistics Missing Values IBM SPSS Missing Values
Uncover missing data patterns, estimate summary statistics and impute missing values. Test this function with a full-feature SPSS trial, or contact us to buy.
Try SPSS Statistics for free See pricing options
Product screen, uncover missing data patterns
What SPSS Missing Values can do for your business

The IBM® SPSS® Missing Values module helps you manage missing values in your data and draw more valid conclusions. Uncover the patterns behind missing data, estimate summary statistics and impute missing values using statistical algorithms. The module helps you build models that account for missing data and remove hidden bias. Survey and market researchers, social scientists, data miners and other professionals rely on IBM SPSS Missing Values to validate their research data.

This module is included with SPSS professional and premium packages. You can also buy it to add to base and standard packages. This module is included in the SPSS professional edition for on premises and in the “Complex sampling and testing” add-on for subscription plans.

Schedule time to discuss how SPSS Missing Values can support your business needs.

Feature spotlights
Multiple imputation procedure

The multiple imputation procedure helps you understand the patterns of missing data in your data set and enables you to replace missing values with plausible estimates. It offers a fully automatic imputation mode that chooses the most suitable imputation method based on characteristics of your data, while also allowing you to customize your imputation model.

Multiple imputation analysis

You can generate possible values for missing values to create several "complete" sets of data. Analytic procedures that work with multiple imputation data sets produce output for each "complete" data set, plus pooled output that estimates what the results would have been if the original data set had no missing values. These pooled results are generally more accurate than those provided by single imputation methods.

Summary of missing values

You can quickly diagnose a serious missing data problem using the overall summary of missing values report. The missing values pattern report provides a case-by-case overview of your data. It displays a snapshot of each type of missing value and any extreme values for each case. The overall summary of missing values report can display pie charts that show different aspects of missing values in the data.

Variable summary and missing value patterns

The variable summary is displayed for variables with at least 10% missing values, and shows the number and percent of missing values for each variable in a table. It also displays the mean and standard deviation for the valid values of scale variables, and the number of valid values for all variables. A patterns chart displays missing value patterns for the analysis variables. Each pattern corresponds to a group of cases with the same pattern of incomplete and complete data.

Technical details
Software requirements
  • For on premises: Purchase the professional edition
  • For Subscription plans: Purchase the “Complex sampling and testing” add-on
See a complete list of software requirements

Hardware requirements
  • Processor: 2 GHz or faster
  • Display: 1024*768 or higher
  • Memory: 4 GB of RAM required, 8 GB of RAM or more recommended
  • Disk Space: 2 GB or more
See a complete list of hardware requirements
Take the next step
Try SPSS Statistics at no cost Compare products and pricing
More ways to explore Documentation Community