Note what you can do with Mean.# and Sum.# to tackle missing values. And also take note of LAG which takes up the value of the preceding case.

COMPUTE y=ABS(x). absolute value of x. ABS(!7) =7.

COMPUTE y=SQRT(x). square root

COMPUTE y=LN(x). natural logarithm

COMPUTE y=LG10(x). base 10 logarithm

COMPUTE y=EXP(x). exponential: ex

COMPUTE y=TRUNC(x). integer part. TRUNC(5.7)=5.

COMPUTE y=RND(x). round to nearest integer. RND(5.7)=6

COMPUTE y=MOD(x,11). remainder after division by 11

COMPUTE y=SUM(x1,x2,x3). sum of 3 variables if at least one is non-missing

COMPUTE y=SUM.5(x1 TO x10). sum of 10 variables if at least 5 are non-missing.

COMPUTE y=MEAN.2(x1,x2,x3). mean of 3 variables if at least 2 are non-missing

COMPUTE y=LAG(x). x from previous case

COMPUTE y=$SYSMIS. sets Y to sysmis.

Source: SPSS for Windows 8, 9 and 10 by Svend Juul

I will try to collect all my SPSS/STATA and other stats notes here!!

## Thursday, 27 October 2011

### Dropping missing values in SPSS

(This needs some more thought and cleaning up)

The SELECT command with the SYSMIS() function can drop all missing cases from the current SPSS data set. Consider the following:

SELECT IF NOT (SYSMIS (amount)). SAVE OUTFILE= 'newfile.sav'.

This example drops all cases whose value of the variable amount is missing, and then saves this data to an SPSS system file called newfile.sav.

If the dataset has more than one coding for missing values, as is often the case for survey data, select all of the different codings for missing values with the AND operator:

SELECT IF NOT (SYSMIS(amount1)) AND NOT (SYSMIS(amount2)). SAVE OUTFILE= 'newfile.sav'.

http://kb.iu.edu/data/afay.html

The SELECT command with the SYSMIS() function can drop all missing cases from the current SPSS data set. Consider the following:

SELECT IF NOT (SYSMIS (amount)). SAVE OUTFILE= 'newfile.sav'.

This example drops all cases whose value of the variable amount is missing, and then saves this data to an SPSS system file called newfile.sav.

If the dataset has more than one coding for missing values, as is often the case for survey data, select all of the different codings for missing values with the AND operator:

SELECT IF NOT (SYSMIS(amount1)) AND NOT (SYSMIS(amount2)). SAVE OUTFILE= 'newfile.sav'.

http://kb.iu.edu/data/afay.html

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