R help - Aug 2004 - Giving a first good impression of R to Social Scientists

Dear all,

in the coming Winter Semester, I will be a teaching assistant for a course
in Survival Analysis. My job will be to do the lab sessions. The software
used for these lab sessions will be R. Most of the students have a
background in social sciences and the only stats package they used so far is
most likely SPSS.
So I assume they might be quite surprised the first time they see R ("where
is my rectangular data window?", "where do I have to click to make a
new
variable?", ...).

That is why would like to ask the experts on this list if anyone of you has
encountered a similar experience and what you could advise to persuade
people quickly that it is worth learning a new software?
I imagined to give them a short presentation about the nice capabilities
what R can do which would be impossible or troublesome with conventional
software like SPSS.[1] The reason is that I want to create an atmosphere
where people have a positive attitude towards learning a new software right
from the beginning. This would make it easier for me and I guess also the
students learn more and faster if they have a positive first encounter with
R.

(Afterwards I plan to introduce them to the basics of R with the help of
Venables/Smith/R Core Team: "An Introduction to R", Dalgaard
"Introductory
Statistics with R" and Krause/Olson "The Basics of S and S-Plus"
before
doing any survival analysis relevant exercises.)

I would appreciate any suggestions!

Thanks for your help,
Roland


[1] I originally thought to show them how easy it is to estimate in R a
Kaplan-Meier-Survival curve in the presence of left truncation, whereas I
have seen no possibility so far to do that in SPSS (that could be also due
to my lack of knowledge using SPSS) but the KM-estimator is a topic during
the course, so I can not use this example.


+++++
This mail has been sent through the MPI for Demographic Rese...{{dropped}}

Hi,

do you know there are several GUI for R? See:

http://www.sciviews.org/_rgui/

and in particular:

http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/

R-Commander is quite like GUI of commercial softwares.
Give a look: they can help your pupils which are able
to use SPSS.
Although I prefer command line, for me is simplier.

Best

Vito
 

Dear all,

in the coming Winter Semester, I will be a teaching
assistant for a course
in Survival Analysis. My job will be to do the lab
sessions. The software
used for these lab sessions will be R. Most of the
students have a
background in social sciences and the only stats
package they used so far is
most likely SPSS.
So I assume they might be quite surprised the first
time they see R ("where
is my rectangular data window?", "where do I have to
click to make a new
variable?", ...).

That is why would like to ask the experts on this list
if anyone of you has
encountered a similar experience and what you could
advise to persuade
people quickly that it is worth learning a new
software?
I imagined to give them a short presentation about the
nice capabilities
what R can do which would be impossible or troublesome
with conventional
software like SPSS.[1] The reason is that I want to
create an atmosphere
where people have a positive attitude towards learning
a new software right
from the beginning. This would make it easier for me
and I guess also the
students learn more and faster if they have a positive
first encounter with
R.

(Afterwards I plan to introduce them to the basics of
R with the help of
Venables/Smith/R Core Team: "An Introduction to R",
Dalgaard "Introductory
Statistics with R" and Krause/Olson "The Basics of S
and S-Plus" before
doing any survival analysis relevant exercises.)

I would appreciate any suggestions!

Thanks for your help,
Roland


[1] I originally thought to show them how easy it is
to estimate in R a
Kaplan-Meier-Survival curve in the presence of left
truncation, whereas I
have seen no possibility so far to do that in SPSS
(that could be also due
to my lack of knowledge using SPSS) but the
KM-estimator is a topic during
the course, so I can not use this example.



http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/

====Diventare costruttori di soluzioni

Visitate il portale http://www.modugno.it/
e in particolare la sezione su Palese
http://www.modugno.it/archivio/cat_palese.shtml

Hi,
> -----Original Message-----
> From:	Vito Ricci [SMTP:vito_ricci at yahoo.com]
> do you know there are several GUI for R? See:
	[...]
> R-Commander is quite like GUI of commercial softwares.
> 
> 
	Yes, I do know the R-Commander. But I did not want to give them a
GUI but rather expose them to the command line after I demonstrated that the
steep learning curve in the beginning is worth the effort for the final
results.

	That is why I wanted to ask the list if anyone has faced the same
situation to persuade students to use R. Are social science students most
impressionable with some nice graphs (e.g. filled.contour) or will they get
a more positive attitude if I used the "R as an overgrown calculator"
like
in Peter Dalgaards book? Or should I write an SPSS script to perform a
certain task and demonstrate how easy, compact, and elegant it is to fulfill
the same job in R? Just telling them "We will use R during our course"
without any explanation would be not a good choice in my opinion.

	As I have written before: I would like the students to trust me that
it is worth to invest some extra energy in the beginning. I do not expect to
receive any prepared demonstration from anyone of you. I am more curious
about your teaching experiences and how you got people enthusiastic to use
this software.

	Thanks,
	Roland



+++++
This mail has been sent through the MPI for Demographic Rese...{{dropped}}

Hi,

I have encountered big difficulties trying to persuade my undergraduate
students, with very "slight" background either in statistics or
computing to
use R instead of SPSS.

 I tried to start with a sort of very, very simple sample session, just for
showing that R is not as complicated as they think and it is worth trying....
The idea was to give them a kind of simple lab guide they could follow at
their own pace, and stimulate them to search in help files, etc... I think it
is important that they get used to try around the examples and documentation
to solve specific problems...


Best
Susana


--
Susana Barbosa
Departamento de Matematica Aplicada
Faculdade de Ci??ncias, Universidade Porto
Rua do Campo Alegre, 687, 4169-007, Porto
Tel: 220 100 840
Fax: 220 100 809

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

-- 
Susana Barbosa
Departamento de Matematica Aplicada
Faculdade de Ci??ncias, Universidade Porto
Rua do Campo Alegre, 687, 4169-007, Porto
Tel: 220 100 840
Fax: 220 100 809

On Thu, 12 Aug 2004, Rau, Roland wrote:
>
> That is why would like to ask the experts on this list if anyone of you has
> encountered a similar experience and what you could advise to persuade
> people quickly that it is worth learning a new software?
One problem is that it may not be true.  Unless these people are going to
be doing their own statistics in the future (which is probably true only
for a minority) they might actually be better off with a point and click
interface.  I'm (obviously) not arguing that SPSS is a better statistical
environment than R, but it is easier to learn, and in 10 or 15 weeks they
may not get to see the benefits of R.


	-thomas

Rau, Roland <Rau <at> demogr.mpg.de> writes:
> 	Yes, I do know the R-Commander. But I did not want to give them a
> GUI but rather expose them to the command line after I demonstrated that
the
> steep learning curve in the beginning is worth the effort for the final
> results.
Note that Rcmdr displays all the underlying generated R code that does
the analysis as it runs so you are exposed to the command line.  This
might pique the interest of students wishing to learn more while giving
an easy-to-use and immediately useful environment for those who just want
to get results in the shortest most direction fashion.

> From: Barry Rowlingson
> 
> Thomas Lumley wrote:
> > On Thu, 12 Aug 2004, Rau, Roland wrote:
> > 
> >>That is why would like to ask the experts on this list if 
> anyone of you has
> >>encountered a similar experience and what you could advise 
> to persuade
> >>people quickly that it is worth learning a new software?
> > 
> 
>   The usual way of teaching R seems to be bottom-up. Here's 
> the command 
> prompt, type some arithmetic, make some assignments, learn about 
> function calls and arguments, write your own functions, write 
> your own 
> packages.
> 
>   Perhaps a top-down approach might help certain cases. People using 
> point-n-click packages tend to use a limited range of analyses. Write 
> some functions that do these analyses, or give them wrappers so that 
> they get something like:
> 
>   > myData = readDataFile("foo.dat")
>     Read 4 variables: Z, Age, Sex, Disease
> 
>   > analyseThis(myData, response="Z",
covariate="Age")
> 
>    Z = 0.36 * Age, Significance level = 0.932
> 
>   or whatever. Really spoon feed the things they need to do. Make it 
> really easy, foolproof.
The problem is that the only `fool' that had been `proof' against is the
one
that the developer(s) had imagined.  One cannot under-estimate users'
ability to out-fool the developers' imagination...

Cheers,
Andy

 
>   Then show them what's behind the analyseThis() function. 
> How its not 
> even part of the R distribution. How easy you made it for a 
> beginner to 
> do a complex and novel analysis. Then maybe it'll "click" for
> them, and 
> they'll see how having a programming language behind their statistics 
> functions lets them explore in ways not thought possible with the 
> point-n-click paradigm. Perhaps they'll start editing 
> analyseThis() and 
> write analyseThat(), start thinking for themselves.
> 
>   Or maybe they'll just stare at you blankly...
> 
> Baz
> 
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide! 
> http://www.R-project.org/posting-guide.html
> 
>

Dear Roland,

Have you looked at Zelig (http://gking.harvard.edu/zelig)?
Several professors in my department are going to use it to teach
R to political science undergraduates and graduate students this
fall.  We just presented it at the Political Methodology
meeting, and will present it again at the American Political
Science Association meeting, so we hope that other departments
will start to use Zelig as a teaching tool (for applied social
science in general, as an alternative to Stata, etc.).

Although a GUI would be good, students won't learn to use R that
way.  I think that the key to getting them to use the command
line interface is to draw an analogy between R and English (or
another language):  There are rules of syntax; here they are; if
you get a "syntax error", you should look for the following
common errors; here are some simple examples and demos that you
can/want to follow (because you're interested in the problem);
and here are the models in a logical format.

Social scientists aren't statisticians, but they're pretty
clever.  They probably had to learn at least one foreign
language in university, and they're probably pretty careful
writers in any language, so making R seem like just another
language will make R seem *easy* to use.

Yours,

Olivia Lau
> On Thu, 12 Aug 2004, Rau, Roland wrote:
> >
> > That is why would like to ask the experts on this list if
anyone of you has
> > encountered a similar experience and what you could advise
to persuade
> > people quickly that it is worth learning a new software?
>
> One problem is that it may not be true.  Unless these people
are going to
> be doing their own statistics in the future (which is probably
true only
> for a minority) they might actually be better off with a point
and click
> interface.  I'm (obviously) not arguing that SPSS is a better
statistical
> environment than R, but it is easier to learn, and in 10 or 15
weeks they
> may not get to see the benefits of R.
>
>
> -thomas
>
>
>
> ------------------------------
>
> Message: 12
> Date: Thu, 12 Aug 2004 16:24:28 +0100
> From: Barry Rowlingson <B.Rowlingson at lancaster.ac.uk>
> Subject: Re: [R] Giving a first good impression of R to Social
> Scientists
> To: "'r-help at stat.math.ethz.ch'" <r-help at
stat.math.ethz.ch>
> Message-ID: <411B8BAC.2050906 at lancaster.ac.uk>
> Content-Type: text/plain; charset=us-ascii; format=flowed
>
> Thomas Lumley wrote:
> > On Thu, 12 Aug 2004, Rau, Roland wrote:
> >
> >>That is why would like to ask the experts on this list if
anyone of you has
> >>encountered a similar experience and what you could advise
to persuade
> >>people quickly that it is worth learning a new software?
> >
>
>   The usual way of teaching R seems to be bottom-up. Here's
the command
> prompt, type some arithmetic, make some assignments, learn
about
> function calls and arguments, write your own functions, write
your own
> packages.
>
>   Perhaps a top-down approach might help certain cases. People
using
> point-n-click packages tend to use a limited range of
analyses. Write
> some functions that do these analyses, or give them wrappers
so that
> they get something like:
>
>   > myData = readDataFile("foo.dat")
>     Read 4 variables: Z, Age, Sex, Disease
>
>   > analyseThis(myData, response="Z",
covariate="Age")
>
>    Z = 0.36 * Age, Significance level = 0.932
>
>   or whatever. Really spoon feed the things they need to do.
Make it
> really easy, foolproof.
>
>   Then show them what's behind the analyseThis() function. How
its not
> even part of the R distribution. How easy you made it for a
beginner to
> do a complex and novel analysis. Then maybe it'll "click" for
them, and
> they'll see how having a programming language behind their
statistics
> functions lets them explore in ways not thought possible with
the
> point-n-click paradigm. Perhaps they'll start editing
analyseThis() and
> write analyseThat(), start thinking for themselves.
>
>   Or maybe they'll just stare at you blankly...
>
> Baz
>
>
>
> ------------------------------
>
> Message: 13
> Date: Thu, 12 Aug 2004 08:28:18 -0700 (PDT)
> From: Jason Liao <jg_liao at yahoo.com>
> Subject: [R] truly object oriented programming in R
> To: r-help at stat.math.ethz.ch
> Message-ID:
<20040812152818.69617.qmail at
web53706.mail.yahoo.com>
> Content-Type: text/plain; charset=us-ascii
>
> Good morning! I recently implemented a KD tree in JAVA for
faster
> kernel density estimation (part of the code follows). It went
well. To
> hook it with R, however, has proved more difficult. My
question is: is
> it possible to implement the algorithm in R? My impression
seems to
> indicate no as the code requires a complete class-object
framework that
> R does not support. But is there an R package or something
that may
> make it possible? Thanks in advance for your help.
>
> Java implementation of KD tree:
>
> public class Kdnode {
>
>         private double[] center; //center of the bounding box
>         private double diameter; //maximum distance from
center to
> anywhere within the bounding box
>         private int numOfPoints; //number of source data
points in the
> bounding box
>
>         private Kdnode left, right;
>
>
> public Kdnode(double[][] points, int split_dim, int [][]
> sortedIndices, double[][] bBox) {
>            //bBox: the bounding box, 1st row the lower bound,
2nd row
> the upper bound
>                 numOfPoints = points.length;
> int d = points[0].length;
>
>                 center = new double[d];
>                 for(int j=0; j<d; j++) center[j] >
(bBox[0][j]+bBox[1][j])/2.;
>                 diameter = get_diameter(bBox);
>
> if(numOfPoints==1) {
>                   diameter = 0.;
>                   for(int j=0; j<d; j++) center[j] points[0][j];
>   left = null;
>   right = null;
> }
> else {
>                   int middlePoint >
sortedIndices[split_dim][numOfPoints/2];
>   double splitValue = points[middlePoint][split_dim];
>
>                   middlePoint >
sortedIndices[split_dim][numOfPoints/2-1];
>                   double splitValue_small >
points[middlePoint][split_dim];
>
>   int left_size = numOfPoints/2;
>                   int right_size = numOfPoints - left_size;
>
>   double[][] leftPoints = new double[left_size][d];
>                   double[][] rightPoints = new
double[right_size][d];
>
>
>   int[][] leftSortedIndices = new int[d][left_size];
>   int[][] rightSortedIndices = new int[d][right_size];
>
>   int left_counter = 0, right_counter = 0;
>   int[] splitInfo = new int [numOfPoints];
>
>   for(int i = 0; i < numOfPoints; i++) {
>     if(points[i][split_dim] < splitValue) {
> for(int j=0; j<d; j++) leftPoints[left_counter][j] points[i][j];
>        splitInfo[i] = right_counter;
>                         left_counter++;
>                     }
>
>     else {
> for(int j=0; j<d; j++) rightPoints[right_counter][j] points[i][j];
> splitInfo[i] = left_counter;
>                         right_counter++;
>                     }
>                   }
> // modify appropriately the indices to correspond to the new
lists
> for(int i = 0; i < d; i++) {
> int left_index = 0, right_index = 0;
> for(int j = 0; j < numOfPoints; j++) {
> if(points[sortedIndices[i][j]][split_dim] < splitValue)
> leftSortedIndices[i][left_index++] = sortedIndices[i][j] -
> splitInfo[sortedIndices[i][j]];
> else    rightSortedIndices[i][right_index++] sortedIndices[i][j]
> - splitInfo[sortedIndices[i][j]];
>                                 }
> }
>
> // Recursively compute the kdnodes for the points in the two
> splitted spaces
> double[][] leftBBox = new double[2][];
> double[][] rightBBox = new double[2][];
>
>                         for(int i=0; i<2; i++) {
>                                 leftBBox[i] > (double[])bBox[i].clone();
>                                 rightBBox[i] >
(double[])bBox[i].clone();
>                             }
>
>                         leftBBox[1][split_dim] splitValue_small;
>                         rightBBox[0][split_dim] = splitValue;
>
>                         int next_dim = (split_dim + 1) % (d);
> left = new Kdnode(leftPoints, next_dim, leftSortedIndices,
> leftBBox);
> right = new Kdnode(rightPoints, next_dim, rightSortedIndices,
> rightBBox);
> }
> }
>
>
>         public double evaluate(double[] target, double delta,
double
> bandwidth) throws Exception
>         {
>
>              double dis_2_center = Common.distance(target,
> center)/bandwidth;
>              double dm = diameter/bandwidth;
>
>              if(dis_2_center >= 1+dm) return 0.;
>              if(numOfPoints==1) return Common.K(dis_2_center);
>
>              /*if(dis_2_center<1)
>              {
>                  double temp2 dm*Common.KDeriv(dis_2_center);
>                  if(temp2<delta) return
> Common.K(dis_2_center)*numOfPoints;
>              } */
>
>              return left.evaluate(target,delta, bandwidth) +
> right.evaluate(target,delta, bandwidth);
>         }
>
>
>          public double get_diameter(double[][] bBox)
>         {
>             double value = 0., diff;
>             for (int i=0; i<bBox[0].length;i++)
>             {
>                 diff = (bBox[1][i] - bBox[0][i])/2.;
>                 value += diff*diff;
>             }
>             return Math.sqrt(value);
>         }
> }
>
> ====> Jason Liao, http://www.geocities.com/jg_liao
> Dept. of Biostatistics, http://www2.umdnj.edu/bmtrxweb
> University of Medicine and Dentistry of New Jersey
> phone 732-235-5429, School of Public Health office
> phone 732-235-8611, Cancer Institute of New Jersey office
> moble phone 908-720-4205
>
>
>
> ------------------------------
>
> Message: 14
> Date: Thu, 12 Aug 2004 15:40:52 +0000 (UTC)
> From: Gabor Grothendieck <ggrothendieck at myway.com>
> Subject: Re: [R] truly object oriented programming in R
> To: r-help at stat.math.ethz.ch
> Message-ID: <loom.20040812T173739-400 at post.gmane.org>
> Content-Type: text/plain; charset=us-ascii
>
> Jason Liao <jg_liao <at> yahoo.com> writes:
>
> :
> : Good morning! I recently implemented a KD tree in JAVA for
faster
> : kernel density estimation (part of the code follows). It
went well. To
> : hook it with R, however, has proved more difficult. My
question is: is
> : it possible to implement the algorithm in R? My impression
seems to
> : indicate no as the code requires a complete class-object
framework that
> : R does not support. But is there an R package or something
that may
> : make it possible? Thanks in advance for your help.
>
> R comes with the S3 and S4 object systems out-of-the-box and
there is an
> addon package oo.R available at:
>
>    http://www.maths.lth.se/help/R/R.classes/
>
> that provides a more conventional OO system.   Its likely that
one or more
> of these would satisfy your requirements.
>
>
>
> ------------------------------
>
> Message: 15
> Date: Thu, 12 Aug 2004 17:56:05 +0200
> From: "Kahra Hannu" <kahra at mpsgr.it>
> Subject: RE: [R] linear constraint optim with
bounds/reparametrization
> To: "Spencer Graves" <spencer.graves at pdf.com>,
"Ingmar Visser"
> <i.visser at uva.nl>
> Cc: Thomas Lumley <tlumley at u.washington.edu>,
R-help at stat.math.ethz.ch
> Message-ID:
> <C9FC71F7E9356F40AFE2ACC2099DE14714963D at MAILSERVER-B.mpsgr.it>
> Content-Type: text/plain; charset="iso-8859-1"
>
> >From Spencer Graves:
>
> >However, for an equality constraint, I've had good luck by
with an objective function that adds something like the
> >following to my objective function:
constraintViolationPenalty*(A%*%theta-c)^2, where
"constraintViolationPenalty" is
> >passed via "..." in a call to optim.
>
> I applied Spencer's suggestion to a set of eight different
constrained portfolio optimization problems. It seems to give a
usable practice to solve the portfolio problem, when the QP
optimizer is not applicable. After all, practical portfolio
management is more an art than a science.
>
> >I may first run optim with a modest value for
constraintViolationPenalty then restart it with the output of
the
> >initial run as starting values and with a larger value for
constraintViolationPenalty.
>
> I wrote a loop that starts with a small value for the penalty
and stops when the change of the function value, when increasing
the penalty, is less than epsilon. I found that epsilon = 1e-06
provides a reasonable accuracy with respect to computational
time.
>
> Spencer, many thanks for your suggestion.
>
> Hannu Kahra
>
>
>
> ------------------------------
>
> Message: 16
> Date: Thu, 12 Aug 2004 17:59:21 +0200
> From: Martin Maechler <maechler at stat.math.ethz.ch>
> Subject: Re: [R] error using daisy() in library(cluster). Bug?
> To: Javier Garcia - CEBAS <rn001 at cebas.csic.es>
> Cc: R-help at stat.math.ethz.ch
> Message-ID: <16667.37849.634789.455341 at gargle.gargle.HOWL>
> Content-Type: text/plain; charset=iso-8859-1
>
> [Reverted back to R-help, after private exchange]
>
> >>>>> "MM" == Martin Maechler <maechler at
stat.math.ethz.ch>
> >>>>>     on Thu, 12 Aug 2004 17:12:01 +0200 writes:
>
> >>>>> "javier" == javier garcia <- CEBAS
<rn001 at cebas.csic.es>>
> >>>>>     on Thu, 12 Aug 2004 16:28:27 +0200 writes:
>
>     javier> Martin; Yes I know that there are variables with
all
>     javier> five values 'NA'. I've left them as they are
just
>     javier> because of saving a couple of lines in the script,
>     javier> and because I like to see that they are there,
>     javier> although all values are 'NA'.  I don't expect
they
>     javier> are used in the analysis, but are they the source
of
>     javier> the problem?
>
>     MM> yes, but only because of "stand = TRUE".
>
>     MM> Yes, one could imagine that it might be good when
>     MM> standardizing these "all NA variables" would work
>
>     MM> I'll think a bit more about it.  Thank you for the
>     MM> example.
>
> Ok. I've thought (and looked at the R code) a bit longer.
> Also considered the fact (you mentioned) that this worked in R
1.8.0.
> Hence, I'm considering the current behavior a bug.
>
> Here is the patch (apply to cluster/R/daisy.q in the *source*
>  or at the appriopriate place in
<cluster_installed>/R/cluster ) :
>
> --- daisy.q 2004/06/25 16:17:47 1.17
> +++ daisy.q 2004/08/12 15:23:26
> @@ -78,8 +78,8 @@
>      if(all(type2 == "I")) {
>   if(stand) {
>              x <- scale(x, center = TRUE, scale = FALSE) #->
0-means
> -            sx <- colMeans(abs(x))
> -            if(any(sx == 0)) {
> +     sx <- colMeans(abs(x), na.rm = TRUE)# can still have
NA's
> +     if(0 %in% sx) {
>                  warning(sQuote("x"), " has constant columns
",
>                          pColl(which(sx == 0)), "; these are
standardized to 0")
>                  sx[sx == 0] <- 1
>
>
> Thank you for helping to find and fix this bug.
> Martin Maechler, ETH Zurich, Switzerland
>
>     javier> El Jue 12 Ago 2004 15:11, MM escribi??:
>
>     >>> Javier, I could well read your .RData and try your
>     >>> script to produce the same error from daisy().
>     >>>
>     >>> Your dataframe is of dimension 5 x 180 and has many
>     >>> variables that have all five values 'NA' (see
below).
>     >>>
>     >>> You can't expect to use these, do you?  Martin
>
>
>
> ------------------------------
>
> Message: 17
> Date: Thu, 12 Aug 2004 16:14:07 +0000 (UTC)
> From: Gabor Grothendieck <ggrothendieck at myway.com>
> Subject: Re: [R] RE: Giving a first good impression of R to
Social
> Scientists
> To: r-help at stat.math.ethz.ch
> Message-ID: <loom.20040812T175128-1 at post.gmane.org>
> Content-Type: text/plain; charset=us-ascii
>
> Rau, Roland <Rau <at> demogr.mpg.de> writes:
>
> > Yes, I do know the R-Commander. But I did not want to give
them a
> > GUI but rather expose them to the command line after I
demonstrated that the
> > steep learning curve in the beginning is worth the effort
for the final
> > results.
>
> Note that Rcmdr displays all the underlying generated R code
that does
> the analysis as it runs so you are exposed to the command
line.  This
> might pique the interest of students wishing to learn more
while giving
> an easy-to-use and immediately useful environment for those
who just want
> to get results in the shortest most direction fashion.
>
>
>
> ------------------------------
>
> Message: 18
> Date: Thu, 12 Aug 2004 09:25:07 -0700
> From: Seth Falcon <sfalcon at fhcrc.org>
> Subject: Re: [R] Approaches to using RUnit
> To: r-help at stat.math.ethz.ch
> Message-ID: <20040812162505.GA23691 at queenbee.fhcrc.org>
> Content-Type: text/plain; charset=us-ascii
>
> On Tue, Aug 10, 2004 at 04:53:49PM +0200, Klaus Juenemann
wrote:
> > If you don't organize your code into packages but source
individual R
> > files your approach to source the code at the beginning of a
test file
> > looks the right thing to do.
>
> Appears to be working pretty well for me too ;-)
>
> > We mainly use packages and the code we use to test packages
A and B,
> > say, looks like
>
> SNIP
>
> > We use the tests subdirectory of a package to store our
RUnit tests
> > even though this is not really according to R conventions.
>
> In an off list exchange with A.J. Rossini, we discussed an
alternative
> for using RUnit in a package.  The idea was to put the
runit_*.R files
> (containing test code) into somePackage/inst/runit/ and then
put a
> script, say dorunit.R inside somePackage/test/ that would
create the
> test suite's similar to the code you included in your mail.
The
> advantage of this would be that the unit tests would run using
R CMD
> check.
>
> In the next week or so I hope to package-ify some code and try
this out.
>
>
> + seth
>
>
>
> ------------------------------
>
> Message: 19
> Date: Thu, 12 Aug 2004 12:25:03 -0400
> From: "Liaw, Andy" <andy_liaw at merck.com>
> Subject: RE: [R] Giving a first good impression of R to Social
> Scientists
> To: "'Barry Rowlingson'" <B.Rowlingson at
lancaster.ac.uk>,
> "'r-help at stat.math.ethz.ch'" <r-help at
stat.math.ethz.ch>
> Message-ID:
> <3A822319EB35174CA3714066D590DCD504AF8214 at usrymx25.merck.com>
> Content-Type: text/plain
>
> > From: Barry Rowlingson
> >
> > Thomas Lumley wrote:
> > > On Thu, 12 Aug 2004, Rau, Roland wrote:
> > >
> > >>That is why would like to ask the experts on this list if
> > anyone of you has
> > >>encountered a similar experience and what you could advise
> > to persuade
> > >>people quickly that it is worth learning a new software?
> > >
> >
> >   The usual way of teaching R seems to be bottom-up. Here's
> > the command
> > prompt, type some arithmetic, make some assignments, learn
about
> > function calls and arguments, write your own functions,
write
> > your own
> > packages.
> >
> >   Perhaps a top-down approach might help certain cases.
People using
> > point-n-click packages tend to use a limited range of
analyses. Write
> > some functions that do these analyses, or give them wrappers
so that
> > they get something like:
> >
> >   > myData = readDataFile("foo.dat")
> >     Read 4 variables: Z, Age, Sex, Disease
> >
> >   > analyseThis(myData, response="Z",
covariate="Age")
> >
> >    Z = 0.36 * Age, Significance level = 0.932
> >
> >   or whatever. Really spoon feed the things they need to do.
Make it
> > really easy, foolproof.
>
> The problem is that the only `fool' that had been `proof'
against is the one
> that the developer(s) had imagined.  One cannot under-estimate
users'
> ability to out-fool the developers' imagination...
>
> Cheers,
> Andy
>
>
> >   Then show them what's behind the analyseThis() function.
> > How its not
> > even part of the R distribution. How easy you made it for a
> > beginner to
> > do a complex and novel analysis. Then maybe it'll
"click"
for
> > them, and
> > they'll see how having a programming language behind their
statistics
> > functions lets them explore in ways not thought possible
with the
> > point-n-click paradigm. Perhaps they'll start editing
> > analyseThis() and
> > write analyseThat(), start thinking for themselves.
> >
> >   Or maybe they'll just stare at you blankly...
> >
> > Baz
> >
> > ______________________________________________
> > R-help at stat.math.ethz.ch mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide!
> > http://www.R-project.org/posting-guide.html

I apologize for joining this discussion late, but I was out of town and just
reviewed postings to R-help. I noticed that there were a couple of other
threads that also touched on similar issues.

Bob Andersen and I have written a paper on using R to teach social
statistics; a copy is at
<http://socserv.socsci.mcmaster.ca/jfox/Teaching-with-R.pdf>. It would be
tedious to rehash the paper in detail here, but I'll make a few brief
points:

(1) I believe that, except in special circumstances, GUIs to statistical
software are best for casual or infrequent use. Even users of SPSS who
intend to use the software seriously would be well advised to learn to write
commands. 

(2) The GUI in the Rcmdr package covers what's typically taught in first and
second social-statistics classes.

(3) The difficulty of moving from one statistical package (or computing
environment) to another shouldn't be confused with learning to use a
particular package (or environment) as a novice. I don't believe that
it's
any more difficult to write R commands than, say, SAS or SPSS commands.

(4) As others have pointed out, the principal advantage of R (or another
statistical computing environment, as opposed to a statistical package) is
its programmability. Nevertheless, R is not difficult to teach and learn
even to those who will not (initially) be writing programs.

John

--------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario
Canada L8S 4M4
905-525-9140x23604
http://socserv.mcmaster.ca/jfox

Hi,
I have data on a group of subjects in different years. I should assume
that observations regarding different individuals are independent but
observations for the same individual in different years are not and I
would like to have an estimated standard error (and variance-covariance
matrix) taking into account this problem.

More in general is there a way in R to run a (robust)regression having
different groups in the observations and specifying that the observation
are independent across groups but not necessarily independent within
groups?

Thanks
a.