James
Assume you have n observations. How about recoding all missing values across
the dataset with a given value, say 987 [or some other value that will not
occur in general in your dataset]. Then producing a cross-tabulation by
variable that gives the sum for each variable. Sort this resulting
cross-tabulation output by the value of the sum for each variable. All
variables with a sum of 'n times 987' are very likely to be the ones with
missing values across every observation. You can then check by running
frequencies on just those variables.
It may seem a little clumsy, but it should work. [ps You can always test
whatever method you choose on a small 'made up' dataset.]
Regards
David
[writing in a purely personal capacity]
-----Original Message-----
From: James Trinder [mailto:[log in to unmask]]
Sent: 20 July 2006 6:12 PM
To: [log in to unmask]
Subject: Variables containing nothing but missing values in SPSS
I was just wondering how it might be possible to produce a list of
variables that contain nothing but missing values in SPSS i.e. those
variables with all values set to system missing. I know how to use the
frequency command but I am currently working with an extremely large
dataset and it would just not be practical to run frequencies for each
variable individually and read the output to determine this manually.
Any help would be greatly appreciated, as it would save me much time.
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