X-From:  <bdperrm1@budget>
Newsgroups: bit.listserv.sas-l
Date:         Tue, 7 Apr 1992 12:07:00 EDT
Reply-To:     bdperrm1%budget@ALBNYDH2.BITNET
From:         bdperrm1%budget@ALBNYDH2.BITNET
Subject:      SAS vs. SPSS Summary - Final Chapter.

David Alderton recently sent me some additional comments regarding the
differences between SPSS and SAS.  Given the apparent interest in this
topic, I am posting it with David's permission and ask that others
with additional information post directly to the list for the benefit
of the dozens of members from across the nation and Europe that have
asked me for summaries of this discussion.

          Mike Perry, New York State Division of the Budget.
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>>>>>>>>>>>>>>>>>>> START D. ALDERTON RESPONSE <<<<<<<<<<<<<<<<<<<<<<<<<<
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>Reply-To: alderton@nprdc.navy.mil

Michael, I just saw your note.  You have probably received a ton of comments
by now, but let me add mine.  I was "raised" on SPSS, converted later to
BMDP, and later still to SAS.  As a user, in my mind, there are three major
differences between SAS and SPSS (SPSSx).
      1.  Database management: just try merging 3 files in SPSS!  This, the
simplist of database techniques requires 2 runs in SPSS; a third if you
want flat file output.  And this is just the beginning.  Fundamentally,
SPSS is a data analysis package and little more.
      2.  Flexibility: while the number of options available under SAS
procs (data steps also, but I'm thinking mostly about procs) is somethings
overwhelming, SPSS allows very little flexibility; worse yet, many decisions
and assumptions are not only hardwired, but in fact, are unspecified.  (I
have forgotten which one, but for years, one of the SPSS ANOVA routines
assumed equal n's in its analysis, and although it was not stated, all
computations were based on this assumption so often the sums of squares
were all wrong -- a whole generation of social scientists reported errant
results!)
       3.  Interaction between procs/data steps/database:  One really slick
thing about SAS is its ability to utilize its own output; something SPSS
can rarely do.  I first turned to SAS because I doing some modeling on
individual subject data, and wanted to use the output from the modeling for
subsequent individual difference analyses.  I was using BMDP at the time
and had to run all the regressions, get the output, then re-input the
parameter estimates.  As you know, SAS can pass output to a database, to
a dataset, and to a subsequent proc (in some cases).

I could go on for pages on many other details but I think that this is a
good classification for the major differences between the systems.  In
support of SPSS I'll say that it is cheaper, easier to learn, produces
much less back strain when moving the manuals, and is sufficient for the
majority of behavioral science research.  SAS is however, by far, the
better of the two systems (actually, the best period: better than SPSS,
BMDP, SYSTAT, etc...).

David.

                          David L. Alderton, Ph.D.
               Navy Personnel Research and Development Center
                         Aptitude Research Division
                          San Diego, CA  92152-6800
                      arpanet: alderton@nprdc.navy.mil
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 | The opinions expressed or implied are mine, are not official, and do not  |
 | necessarily reflect the views of the Navy Department or the US Government |
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