Date:         Mon, 15 Dec 2008 13:57:30 -0800
Reply-To:     HBaize <HBaize@buttecounty.net>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         HBaize <HBaize@buttecounty.net>
Subject:      Re: Syntax color code issues
In-Reply-To:  <E1184203-13C1-420D-A438-20B18A60E277@mac.com>
Content-Type: text/plain; charset=us-ascii

I didn't mean to offend GUI users, but I have my opinions.
We don't need to repeat the well documented pros and cons of
GUI versus code.

As you say, nothing is "always" the most efficient approach,
but let us not miss the irony. This thread is about how
the editor has implemented support for color coding of syntax.

>>On the other
hand, there are lots of people who get wildly different datasets at
frequent intervals, sometimes with thousands of variables, and do
different analyses on each dataset, then never see those data or
analyses again. <<

I couldn't imagine a stronger argument for using syntax. If they were
wise they would save their syntax to document what they did with
those "wildly different data sets." Oh wait they can't,
they're using GUI. :-)

I can't even begin to address your dismissive attitude toward psychiatric
epidemiology or mental health service research as mere "patient data." ;-)



Ian Martin-2 wrote:
>
> I can't comment upon the colour coding issue since V.17 is not yet
> available through my institution.
>
> However, I will say that after 30 years of using SPSS, I have now
> mostly "broken free" of using the syntax editor, and now usually rely
> on GUI. The use of one or the other is not necessarily the mark of
> better expertise, but rather of the demands upon the user, and the
> user's workflow.  I have written syntax in SPSS and many other
> programmes, but it is NOT always the most efficient approach. I do
> not feel the GUI or those who use it -- for whatever reason -- merit
> the dismissive comments I hear from time to time on this listserv.
>
> I can quite understand that typing syntax is an efficient method for
> those engaged in repetitive analyses of the same or similar datasets,
> such as quarterly or monthly sales or patient data.  On the other
> hand, there are lots of people who get wildly different datasets at
> frequent intervals, sometimes with thousands of variables, and do
> different analyses on each dataset, then never see those data or
> analyses again.
>
> regards,
> Ian Martin
>
>
> Ian D. Martin, Ph.D.
> Aquatic Ecologist
>
>
>
>
>

--
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