Re: Propensity Scores
- To: mathgroup at smc.vnet.net
- Subject: [mg125590] Re: Propensity Scores
- From: Barrie Stokes <Barrie.Stokes at newcastle.edu.au>
- Date: Tue, 20 Mar 2012 02:21:35 -0500 (EST)
- Delivered-to: email@example.com
- References: <201203170750.CAA05061@smc.vnet.net>
As long-time Mathematican and a long-time Bayesian, a few thoughts.
Mathematica is (at least) a massive CAS (Computer Algebra System), with
lots of mathematical knowledge built-in, and is also a marvellous
programming system for *very* high level coding, algorithm development,
Having looked at the paper you are reading, I note in the synopsis the
author says, in part:
"The estimates of mean effect obtained with *five* (my emphasis)
different techniques were compared and nonparametric bootstrap was
recommended as superior tool for propensity score analyses."
It's enormously frustrating (given the degree of depth in Mathematica
documentation) to realize the absence in Mathematica of a commonly used
statistical function in SAS and STATA, pointing to the real difference
in need between mathematicians and statisticians to impute missing data
from large datasets using bootstrapping."
I think you*ve put your finger on it. There *are* myriad "real
difference in need between mathematicians and statisticians", and that
is reflected in the difference between SAS and Mathematica. Mathematica
is not in the first instance a statistics package, but you can do
advanced mathematical (i.e., symbolical) statistics in it that you
can*t do in a non-CAS system like SAS. To some extent (Mathematica
has fantastic numerical functionality) it*s horses for courses.
I don*t think you should expect that Mathematica should come with
scores or even hundreds of different and very specific statistical model
fitting procedures built-in.
If I want to use the procedures built in to SAS, Stata, etc., on data
to hand, I use them as is. If I want to try a variation on a theme, or
produce a particular graphic, I turn to Mathematica and code it myself.
(Mathematica has full matrix algebra capability for multivariate
Logistic Regression is essentially built-in to Mathematica .
You also say:
"For whatever reason, I assumed otherwise since Mathematica so
exquisitely lends itself to predicting the pathways of cellular
Hmm. There is a, er, well known connection between cellular automata
and Mathematica that possibly explains that observation.
But you can*t expect that Mathematica has ready-made versions of most
of the algorithms in most scientific fields. The tools are there,
And some Google code searching sometimes turns up something useful.
Jerry-rigged? Jerry-rigged? Never. Carefully coded, you mean.
after a spot of Googling.
>>> On 17/03/2012 at 6:50 pm, in message
<201203170750.CAA05061 at smc.vnet.net>,
<sylviahobbs at aol.com> wrote:
> Newbie Here! Finally, I have my very own Mathematica license, to have
> hold until death do us part. We are already arguing over the best way
> construct a propensity score given the absence of a dedicated
> Mathematica. It's enormously frustrating (given the degree of depth
> Mathematica documentation) to realize the absence in Mathematica of a
> commonly used statistical function in SAS and STATA, pointing to the
> difference in need between mathematicians and statisticians to impute
> data from large datasets using bootstrapping. For whatever reason, I
> otherwise since Mathematica so exquisitely lends itself to predicting
> pathways of cellular automata. Mathematica license and I are on
> here in Boston for St. Paddy's weekend reading aloud to each other
> very nice 2009 paper on the impact of exclusion decisions in random
> by Maciej G=C3=B3rkiewicz published in the Biocybernetics and
> Engineering entitled "Usi!
> ng Propensity Score with Receiver Operating Characteristics and
> Evaluate Effect Size in Observational Studies."
> My question is to the Bayesians out there, what Mathematica functions
> you jerry-rigged for propensity scoring? Holla Back!
> Sylvia Hobbs
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