Date: Tue, 10 Aug 2010 21:48:03 +0200
Reply-To: John F Hall <johnfhall@orange.fr>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: John F Hall <johnfhall@orange.fr>
Subject: Re: st: Re: Your paper on Stata,SAS and SPSS
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Alan
I only joined the list two days ago, so I haven't had a chance to find much
Stata syntax to set alongside SPSS. Listers have sent one or two
one-liners, but with no accompanying output examples.
I'm talking about reading from a raw data matrix, adding variable and value
labels, declaring missing values, data transformations, index construction
and the like (possibly via correlation) followed by simple analysis like
frequency counts, barcharts and contingency tables using %%, not fancy
multivariate inferential statistics. Had I still been teaching, that would
have come much later in my course, but far too late for the survey report
that had to be on the client's desk by yesterday.
You're welcome to download data sets and tutorials from my site and offer
Stata examples to set alongside the SPSS syntax and output (no GUI for me:
far too cumbersome, complex and tiresome).
John Hall
http://surveyresearch.weebly.com
----- Original Message -----
From: Alan Acock
To: statalist@hsphsun2.harvard.edu
Cc: Michael.Norman.Mitchell@gmail.com ; spssx-l@listserv.uga.edu ; Bruce
Weaver
Sent: Tuesday, August 10, 2010 5:43 PM
Subject: Re: st: Re: Your paper on Stata,SAS and SPSS
John Hall indicates that with the limited math/statistics background of his
students, the "syntax examples I have seen in Stata, . . . would easily put
(them) off." I'm not sure what examples John has seen. Often those shared on
statalist are technical and not appropriate to beginning students. If you
think about a basic introductory research courses in the social sciences,
the actual Stata commands that would be relevant are vastly simpler than
those used in SPSS or SAS. For SPSS readers who don't appreciate this, here
are a few
examples they might compare to the lengthy syntax needed by SPSS
(chi-square test)
.table var1 var2, chi2
(independent t-test)
.ttest var1 var2
(grouped t-test)
.ttest var1, by(gender)
(Correlation matrix)
.corr var1 - var10
(OLS regression)
.regress y x1 x2 x3, beta
(logistic regression)
.logit y x1 x2 x3, or
If they get a little more advanced and do a Poisson regression, compare the
SPSS command to do a Poisson regression to Stata's--Really--try it in SPSS
.poisson y x1 x2 x3
How about doing a principal component "factor" analysis--the default type in
SPSS. In Stata the command is:
.factor x1 -x10, pcf
Then, if you want a varimax rotation you have the post estimation command
.rotate
Stata's goal is "type a little, get a little." The output wastes far less
space than does SPSS. There are options and post estimation commands for
more advance users. For example, if you want alpha for a 10-item sale you
would enter
.alpha var1 - var10
If you wanted item analysis like SPSS or SAS provide, you would enter
.alpha var1 - var10, item
Of course, Stata has excellent menus, but the reason Stata users don't use
them as much as SPSS users is less the acknowledged elegance of the SPSS
menus than it is the rigid structure of Stata commands resulting in much
simpler command structure (syntax) than is found in SPSS. I suspect that if
John listed all the procedures he taught in his research methods course, the
Stata commands could be all listed on a single page.
Although Stata is vastly more powerful than SPSS for advanced statistical
applications (as well as a fraction of the cost), Stata is also much less
cumbersome for elementary applications. I was motivated to write my "Gentle
Introduction to Stata" (StataPress), because many books about Stata focused
on advanced applications and many social/behavioral scientists had the
notion that Stata was just for advanced users. I believe that the advantages
of Stata are even greater for beginners--not to mention offering them
greater opportunity for growth.
Alan Acock
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