```Date: Sun, 4 Sep 2005 13:27:58 -0300 Reply-To: Hector Maletta Sender: "SPSSX(r) Discussion" From: Hector Maletta Subject: Re: Combining Variable Scores Comments: To: "Frank J. Gallo" In-Reply-To: <0IMA00G01RJXWLD0@vms046.mailsrvcs.net> Content-Type: text/plain; charset="US-ASCII" 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 > > __________ Informacisn de NOD32 1.1208 (20050902) __________ > > Este mensaje ha sido analizado con NOD32 Antivirus System > http://www.nod32.com > > ```

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