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How do you use imputed data in SPSS?
Impute Missing Data Values (Multiple Imputation)
- Select at least two variables in the imputation model.
- Specify the number of imputations to compute.
- Specify a dataset or IBM® SPSS® Statistics-format data file to which imputed data should be written.
How do you enter pool data in SPSS?
Click Data -> Split File. In the dialog box select “Imputation_” and move it to “Groups Based On:” box. Check “Compare Groups”. Now any analysis that you run should get run on Original Data, Iteration No 1 data, Iteration No 2 data… and the pooled data.
How does SPSS deal with missing data?
Cases with missing values are deleted listwise, i.e., observations with missing values on any of the variables in the analysis are omitted from the analysis. Cases with any missing value are excluded from any single complete ANOVA design in which the missing value is encountered.
How to save multiple imputed data sets as SPSS files?
My question is how to save the multiple imputed data sets as SPSS files for later analyses. Any help would be greatly appreciated. My recommendation would be to save each imputed dataset as a CSV file, then load the CSV files in SPSS and save them as SPSS datasets.
How to generate syntax for datasets in SPSS?
Alternatively, if you want to generate SPSS syntax to load the datasets automatically, you could try the foreign package, like this: Using this code, you would get 5 data files (saved as .txt files), and 5 syntax files to load the .txt files into SPSS.
What happens when a dataset is multiple imputed?
Than SPSS recognizes the dataset as an “imputed” dataset and is able to generate pooled analyses results. If SPSS does not recognize the dataset as a multiple imputed dataset, the data will be treated as one large dataset.
What to do when data is split by imputation?
Once your data is split by the “imputation” variable, SPSS should recognize that your dataset is multiply imputed and provide pooled estimates automatically (for the analyses that support multiple imputation in SPSS). I hope that helps! First thank you for your unconditional help.