Build better models when you estimate missing data
IBM® SPSS® Missing Values software is used by survey researchers, social scientists, data miners, market researchers and others to validate data. The software allows you to examine data to uncover missing data patterns, then estimate summary statistics and impute missing values using statistical algorithms.
With SPSS Missing Values software, you can impute your missing data, draw more valid conclusions and remove hidden bias.
Quickly diagnose missing data imputation problems using diagnostic reports.
Replace missing data values with estimates using a multiple imputation model.
Display and analyze patterns to gain insight and improve data management.
Quickly diagnose missing data imputation problems
Examine data from different angles using six diagnostic reports.
Diagnose missing data using the data patterns report, which provides a case-by-case overview of your data.
Determine the extent of missing data and any extreme values for each case.
Replace missing data values with estimates
Understand missing patterns in your data set and replace missing values with plausible estimates.
Benefit from an automatic imputation model that chooses the most suitable method based on characteristics of your data, or customize your imputation model.
Model the individual data sets that are created, using techniques such as linear regression or expectation maximization algorithms, to produce parameter estimates for each.
Obtain final parameter estimates by pooling estimates and computing inferential statistics that take into account variation within and between imputations.
Display and analyze patterns
Display missing data for all cases and all variables using the data patterns table.
Determine differences between missing and non-missing groups for a related variable with the separate t-test table.
Assess how much the missing data for one variable relates to the missing data of another variable using the percent mismatch of patterns table.
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