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Re: st: Two wishes


From   Mark Orr <mo2259@columbia.edu>
To   Statalist <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Two wishes
Date   Tue, 23 May 2006 00:47:20 -0400 (EDT)

The S family, (R, s-plus) stats packages serve as object-oriented languages, in addition to stats packages. This combination is unmatched in flexibility and programming power. Furthermore, when you think of each data set as a single variable, then there is no confusion as to what is what. To be more specific, see all-caps text comments below.


I'm curious: (1) What could you accomplish under such a setup that
you cannot currently (given the many data management commands already
in Stata)? VERY SIMPLE AND POWERFUL PROGRAMMING IF COMING FROM OTHER
OBJECT-ORIENTED PROGRAMMING LANGUAGES. (2) How would one prevent data management complications

(same name for different variables in different datasets; specifying
which dataset(s) to write to, frequency and/or sample period
mismatches, etc.) that do not arise under the current setup? SIMPLY
NEST VARIABLE NAMES, SO THAT THE SAME VARIABLE V IN DATASETS X,Y,Z, IS REALLY THOUGH OF AS X$V, Y$V, AND Z$V>

--------------------------------------------------------------------------------

I think that Stata loads the dataset into memory in order to allow certain
efficiencies (e.g., vectorized operations) that wouldn't be possible
otherwise--i.e., operating on the dataset file one observation at a time.
NO, R CAN DO THIS.


I'm curious:  does *any* data-management/statistical analysis software
package load more than one entire dataset in memory at one time?  Maybe
Raphael meant:  to have more than one dataset file open for manipulation at
a time, such as what SAS does or perhaps what relational database management
systems do.  And, for that matter, you can emulate the same from within
Stata, using the -odbc- suite of commands and SQL.  Unlike SAS, you cannot,
however, analogously invoke SQL statements on native Stata dataset files.
But, as Michael mentioned, it's not certain that you would frequently need
to, given Stata's repertoire of data-management commands.
R, S-PLUS MAKE THIS MUCH SIMPLER. OF COURSE, I PREFER STATA FOR SOME WORK, R FOR OTHER WORK. BOTH HAVE UNIQUE STRENGTHS.

-Mark Orr


~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Mark G. Orr, Ph.D.
Department of Population and Family Health
Columbia University
60 Haven Ave., B-2
New York, NY 10032

718-414-5151
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