Date: Tue, 16 Mar 2010 01:32:24 -0600
Reply-To: Alan Churchill <alan.churchill@SAVIAN.NET>
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: Alan Churchill <alan.churchill@SAVIAN.NET>
Subject: Re: DDE and macro recall
Content-Type: text/plain; charset="iso-8859-1"
HoboCopy looks like an interesting utility. This may come in handy for COM
locked apps like Office.
Insofar as R and perl are concerned, I do not think most SAS users would use
perl. It is simply way too low-level. I find similar resistance to C# which
is probably more friendly due to Visual Studios and pure OOP.
R is only needed by the stat guys and they tend to like what they are
accustomed to (from my experience).
I encourage alternative technologies because it helps on lots of fronts but
the above is simply my observations after working with SAS users for 20+
Office: (719) 687-5954
Cell: (719) 310-4870
From: SAS(r) Discussion [mailto:SAS-L@LISTSERV.UGA.EDU] On Behalf Of
Sent: Monday, March 15, 2010 2:06 PM
Subject: Re: DDE and macro recall
On Mar 15, 9:54 am, montura <montura...@gmail.com> wrote:
> PERL and R?
> You must drunk. Who the hell needs that?
I am not sure where Microsoft is going with DDE(see below), but this may
interest some readers.
What happened to DDE Share?
Applies to all editions of Windows Vista
If you used previous versions of Windows, you might know DDE Share as a tool
for managing the way programs communicate and share data over a network. DDE
Share is not available in this version of Windows because it has been
replaced by other methods for communicating and sharing data among
In the past there was no way to copy a networked shared excel spreadsheet
while multiple users were updating the file, this is why I needed DDE.
Vista has something called hobocopy? to copy 'exclusive open' files? I am
Also the list of R users now has some very heavey weight 'past' SAS power
users? Note Micheal Freindly, not to mention Frank Harrel and others.
They can't all be wrong.
The list below is only about 1/5th of the 'new/updated' packages in R last
Zack W. Almquist
US Census 2000 Block Group shapefiles and additional demographic data
from the SF1 100 percent files. This data set contains polygon files
in lat/lon coordinates and the corresponding demographic data for a
number of different variables.
Provides additional data sets, methods and documentation to complement
the vcd package for Visualizing Categorical Data.
General Non-linear Optimization Using Augmented Lagrange Multiplier
* saws (0.9-3.1)
Tests coefficients with sandwich estimator of variance and with small
samples. Regression types supported are gee, cox regression, and
conditional logistic regression.
Dirk Eddelbuettel and Romain Francois
Examples for Seamless R and C++ integration The Rcpp package contains
a C++ library that facilitates the integration of R and C++ in
various ways. This package provides examples.
AC Del Re
This is an R-Commander plug-in for the MAd package (Meta-Analysis with
Mean Differences). This package enables the user to conduct a
meta-analysis in a menu-driven, graphical user interface environment
(e.g., SPSS), while having the full statistical capabilities of R
and the MAd package. The MAd package itself contains a variety of
useful functions for conducting a research synthesis with mean
differences data. One of the unique features of the MAd package is
in its integration of user-friendly functions to complete many of
the statistical steps involved in a meta-analysis with mean
differences. It uses recommended procedures as described in The
Handbook of Research Synthesis and Meta-Analysis (Cooper, Hedges, &
Rune Haubo B Christensen
This package implements likelihood based models for ordinal (ordered
categorical) data based on cumulative probabilities in the framework
of cumulative link models. This includes the important proportional
odds model but also allows for general regression structures for
location as well as scale of the latent distribution, i.e. additive
as well as multiplicative structures, structured thresholds
(cut-points), nominal effects and flexible link functions. Further,
a range of estimation procedures and a range of auxiliary functions
Place-holder package (roughly speaking an empty package) for finding
clusters in multivariate timeseries. Full implementation pending.
The MplusAutomation package leverages the flexibility of the R
language to automate latent variable model estimation and
interpretation using Mplus, a powerful latent variable modeling
program developed by Muthen and Muthen (www.statmodel.com).
Specifically, MplusAutomation provides routines for creating related
groups of models, running batches of models, and extracting and
tabulating model parameters and fit statistics.