Allowable Syntax

If you have a lot of legacy syntax from IBM® SPSS® Statistics or are familiar with the data preparation features of IBM SPSS Statistics, you can use the Statistics Transform node to run many of your existing transformations. As a guideline, the node enables you to transform data in predictable ways--for example, by running looped commands or by changing, adding, sorting, filtering, or selecting data.

Examples of the commands that can be carried out are:

Compute random numbers according to a binomial distribution:
```
COMPUTE newvar = RV.BINOM(10000,0.1)
```

Recode a variable into a new variable:

RECODE Age (Lowest thru 30=1) (30 thru 50=2) (50 thru Highest=3) INTO AgeRecoded

Replace missing values:

RMV Age_1=SMEAN(Age)

The IBM SPSS Statistics syntax that is supported by the Statistics Transform node is listed below.

Command Name
`ADD VALUE LABELS`
`APPLY DICTIONARY`
`AUTORECODE`
`BREAK`
`CD`
`CLEAR MODEL PROGRAMS`
`CLEAR TIME PROGRAM`
`CLEAR TRANSFORMATIONS`
`COMPUTE`
`COUNT`
`CREATE`
`DATE`
`DEFINE-!ENDDEFINE`
`DELETE VARIABLES`
`DO IF`
`DO REPEAT`
`ELSE`
`ELSE IF`
`END CASE`
`END FILE`
`END IF`
`END INPUT PROGRAM`
`END LOOP`
`END REPEAT`
`EXECUTE`
`FILE HANDLE`
`FILE LABEL`
`FILE TYPE-END FILE TYPE`
`FILTER`
`FORMATS`
`IF`
`INCLUDE`
`INPUT PROGRAM-END INPUT PROGRAM`
`INSERT`
`LEAVE`
`LOOP-END LOOP`
`MATRIX-END MATRIX`
`MISSING VALUES`
`N OF CASES`
`NUMERIC`
`PERMISSIONS`
`PRESERVE`
`RANK`
`RECODE`
`RENAME VARIABLES`
`RESTORE`
`RMV`
`SAMPLE`
`SELECT IF`
`SET`
`SORT CASES`
`STRING`
`SUBTITLE`
`TEMPORARY`
`TITLE`
`UPDATE`
`V2C`
`VALIDATEDATA`
`VALUE LABELS`
`VARIABLE ATTRIBUTE`
`VARSTOCASES`
`VECTOR`