*SPSS syntax commonly used in our lab.

*Key:
UPPERCASE = Universal
lowercase = project specific
italicized = multiple functions possible.


*Combining SAS files across databases.

FILE HANDLE project_name/NAME ='intended_project_file_location'.

GET SAS DATA='projectname/filename_a.XPT'.
DATASET NAME name_dataset_a WINDOW=FRONT.
DATASET ACTIVATE name_dataset_a.
SORT CASES BY identifying_variable(A).
SAVE OUTFILE='project_name/name_dataset_a.SAV'
/KEEP =  identifying_variable variable_1 variable_2 variable_n
/COMPRESSED.

GET SAS DATA='projectname/filename_b.XPT'.
DATASET NAME name_dataset_b WINDOW=FRONT.
DATASET ACTIVATE name_dataset_b.
SORT CASES BY identifying_variable(A).
SAVE OUTFILE='projectname/name_dataset_b.SAV'
/KEEP =  identifying_variable variable_3 variable_4 variable_n
/COMPRESSED.

		*(Repeat for additional files).

MATCH FILES
/file = 'project_name/name_dataset_a.SAV/'
/file = 'project_name/name_dataset_b.SAV/'
/by SEQN.
EXECUTE.

SAVE OUTFILE='project_name/second_name.SAV'
/COMPRESSED.


*Renaming variables.

RENAME VARIABLES (name_a = name_b).
EXECUTE.


*Changing values.

RECODE variable_a (old_value = new_value).
EXECUTE.


*Creating or editing variables based on one existing variable.

IF (variable_a condition value_a) variable_b = value_b.
EXECUTE.


*Creating or editing variables based on multiple existing variables.

COMPUTE variable_a=variable_b function variable_c.
EXECUTE.

		*Or.

COMPUTE variable_a=function(variable_b,variable_c,variable_n).
EXECUTE.


*Filtering.
COMPUTE FILTER_$=(filtering_variable condition value_a).
FILTER BY FILTER_$
EXECUTE.