Added ability to handle missing values in SPSS Statistics

The 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 requires a Statistics Base license.

Diagnose missing data problems quickly

Examine data from different angles using diagnostic reports. Determine the extent of missing data and any extreme values with a case-by-case overview.

Replace data values with estimates

Use a multiple imputation model to understand patterns and replace values; it helps you choose the most suitable method. Use linear regression or expectation maximization algorithms among others.

Gain insight and improve data management

Display missing data for all cases and variables. Determine differences between missing and non-missing groups. Assess how missing data of a variable relates to missing data of another.

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Impute Missing Data Values variable selection
Impute Missing Data Values variable selection
Impute Missing Data Values Output settings
Impute Missing Data Values Output settings
Imputation Models table output
Imputation Models table output
MVA table output
MVA table output

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