Date: Sun, 4 Sep 2005 13:27:58 -0300
Reply-To: Hector Maletta <hmaletta@fibertel.com.ar>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Hector Maletta <hmaletta@fibertel.com.ar>
Subject: Re: Combining Variable Scores
In-Reply-To: <0IMA00G01RJXWLD0@vms046.mailsrvcs.net>
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Frank,
What do you mean by "combining" the scores? As you know, there are different
ways to do that. One simple way is just obtaining the average or sum of
variable scores, but this would give all variables the same weight. A more
elaborate way is factor analysis or some variant of it: if all your
variables reflect one underlying factor or trait, then the first factor
extracted should account for a large portion of total variance in your 37
variables, and the scores for that first factor may be used as a single
variable representing the main component of the common variance in your
variables.
Once you have your final score for the synthetic variable representing your
37 original variables, obtaining the summary measures you mention is quite
easy with the FREQUENCIES or DESCRIPTIVES command. In your case FREQUENCIES
is better because you want the quartiles too.
To summarize:
1. Obtain a single variable representing your 37 scores.
1.1. Obtain it as a simple average.
COMPUTE MEANSCOR=MEAN(LABEL1 TO LABEL37).
If all your 37 variables use the same scale (say, 1 to 5) this may
be enough. If they have different ranges and units, you may better
standardize them to have zero mean and unit standard deviation. This can be
done with the SAVE option in the DESCRIPTIVE command, applied BEFORE the
COMPUTE. The SAVE keyword will create 37 new variables named ZLABEL1 to
ZLABEL37, which will be the standardized version of your variables.
DESCRIPTIVES LABEL1 TO LABEL37/SAVE.
COMPUTE MEANSCOR=MEAN(ZLABEL1 TO ZLABEL37).
1.2. Obtain it by means of FACTOR ANALYSIS:
FACTOR VARIABLES LABEL1 TO LABEL37/PRINT ALL/SAVE REG FASCOR.
This would extract all factors with eigenvalues above 1, and would
save the scores to the file under new variables named FASCOR1 to FASCORk
(where k is the last factor extracted). In the output look at the VARIANCE
EXPLAINED table. Judging from the contribution of the first factor to
explaining all variance in the original variables, you may decide whether
the contribution of the first factor is much larger than the second and
later factors, or perhaps your variables are in fact measuring two or more
different underlying factors of similar importance.
2. Once you have a single score, say FASCOR1 or MEANSCOR, you may know the
main statistics by using FREQUENCIES:
FREQUENCIES FASCOR1 /format notable/ntiles 25/statistics all.
This would not produce an actual frequency distribution (too many
values for that), but will give you the quartiles and all the summary
measures you want (and some more).
Hector
> -----Original Message-----
> From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU]
> On Behalf Of Frank J. Gallo
> Sent: Sunday, September 04, 2005 11:48 AM
> To: SPSSX-L@LISTSERV.UGA.EDU
> Subject: Combining Variable Scores
>
> Hi All,
>
>
>
> Still green at writing syntax, and I am hoping that someone
> can suggest some syntax for the following run:
>
>
>
> -- I have 37 variables (label1 - label37)
>
> -- sample: n = 50 cases
>
> -- I would like to combine the variable scores and then
> compute the mean, median stdev, min, max, Q1 and Q3
> statistics for the sample (n=50).
>
>
>
> Your help is greatly appreciated.
>
> Frank
>
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