UCLA Academic Technology Services HomeServicesClassesContactJobs
Search

SPSS Class Notes
Managing Data


1.0 Demonstration and explanation

Example 1.1 - Honors Thesis

Let's pretend that we are working on our honors thesis and that we want to study just "good readers", those with reading scores 60 or higher. We will open the file and then "select cases" to include the students with reading scores of 60 or higher.

Notice that the undesired cases have now been deleted.  Now we will save our data.

Example 1.1 continued - keeping variables

We want to keep just some variables, including id female read and write.  We keep these variables in the same procedure that we use to save the data file.

Notice you can also choose keep all if that is more helpful to you.

Example 1.2 Masters Thesis

Let's suppose we are working on our masters thesis.  The data are located in a folder called c:\spss\masters and there are two files in this folder, one for the males (hsmale.sav) and one for the females (hsfemale.sav).  We would like to combine these files.

Example 1.3 Dissertation

Now let's suppose that we are working on our dissertation.  The data are in a folder called c:\spss\diss and there are two files in this folder, one with the demographic information (hsdem.sav) and one with the test scores (hstest.sav).  We would like to match merge these files based on id.  Before we can match merge these files, we need to open each file, sort it on id, and then save the sorted file.

Now that we have sorted and saved the first file (hsdem.sav), we will do the same thing for the second file (hstest.sav).

Finally, we will open the first file (hsdem.sav) and merge it with the second file (hstest.sav).  We will save the merged data file with the name hsdiss.sav.

2.0 Syntax version

* working on honors thesis.
* want to make a subset just keeping those who have read >= 60.
get file "c:\spss\hs1.sav".

* assuming we already have a folder called "c:\spss\honors".
select if read >=60.
descriptives 
 /var=read.
save outfile "c:\spss\honors\hsgoodread.sav".

* pretend we have 2000 variables and we want to keep just some of the variables.
* we want to keep just the variables id female read write.
save outfile = "c:\spss\honors\hskept.sav" 
 /keep=id  female read write.
display names.
get file "c:\spss\honors\hskept.sav".
display names.

* extra example not in point and click.
* we want to drop just the variables ses and prog.
get file "c:\spss\honors\hsgoodread.sav".
save outfile "c:\spss\honors\hsdropped.sav" 
 /drop=ses prog.
display names.
get file "c:\spss\honors\hsdropped.sav".
display names.

* have one file with males, females in another file and need to "append" the files.
get file "c:\spss\masters\hsmale.sav".
freq 
 /var=female.

add files 
 /file=* 
 /file="c:\spss\masters\hsfemale.sav".
freq 
 /var=female.

save outfile "c:\spss\masters\hsmasters.sav".

* one file has demographic scores, the other has test scores and we want to "match merge" the files.
get file "c:\spss\diss\hsdem.sav".
list cases from 1 to 10.

sort cases by id.
save outfile "c:\spss\diss\hsdem.sav".

get file "c:\spss\diss\hstest.sav".
list cases from 1 to 10.

sort cases by id.
save outfile "c:\spss\diss\hstest.sav".

get file "c:\spss\diss\hsdem.sav".
match files 
 /file=* 
 /in=fromdem 
 /file="c:\spss\diss\hstest.sav" 
 /in=fromtest
 /by id.

list cases from 1 to 10.

list variables id fromdem fromtest.
crosstab 
 /tables=fromdem by fromtest.

save outfile "c:\spss\diss\hsdiss.sav".

3.0 For more information


How to cite this page

Report an error on this page

UCLA Researchers are invited to our Statistical Consulting Services
We recommend others to our list of Other Resources for Statistical Computing Help
These pages are Copyrighted (c) by UCLA Academic Technology Services


The content of this web site should not be construed as an endorsement of any particular web site, book, or software product by the University of California