R-sig-Epi Digest, Vol 45, Issue 1

Sat, Sep 4, 2010 12:36 AM

Further to this thread:

It seems that the only shortcoming in R in relation to epidemiological practise is the data entry side. Which can be excellently handled by EpiData, which can output Stata data files (.dta) that are seamlessly imported to R via read.dta() from the foreign package.

I doubt there are anything on the analysis side in EpiInfo which is not in R, so the only issue is really the accessibility where the learning curve for R (or any command driven package) is steep.
But this is really just a feature of science: You must be able to reproduce your results, so you have to generate code which will re-do your analyses. So the point-and-click systems should not be used in scientific reporting anyway. Some of these systems leave a trace, but the code left is normally largely impenetrable, so not really a documentation of anything but the time you spent operating the mouse.

Best regards,
Bendix
Epi maintainer

-----Original Message-----
From: r-sig-epi-bounces at stat.math.ethz.ch 
[mailto:r-sig-epi-bounces at stat.math.ethz.ch] On Behalf Of 
Pedro Emmanuel Alvarenga Americano do Brasil
Sent: 4. september 2010 05:47
To: r-sig-epi at stat.math.ethz.ch
Subject: Re: [R-sig-Epi] R-sig-Epi Digest, Vol 45, Issue 1

Kevin,

Although I thought at first it sound like a nice idea it also 
seems a tough task!!! Unfortunately Im a epidemiologist and I 
do not fell able to develop complex stuff in R.

I did use very few times EpiInfo long ago and in the last 
four year I invested a lot of time in R due to my PhD project.

I wondered about some points in this idea of yours.
R is a very powerful and complex tool, so what is epiinfo 
able to do that R is not?
In the other way around, what is R is able to do that epiInfo is not?

My guess is that R is able to do most, if not all, analysis 
epiinfo can.
Thus what are the weak points? EpiInfo is directod to users (most
epidemiologist) which may have basics to moderate 
understanding of statistics and like to freindly data entry 
and dropdown menus and dialog boxes with more intuitive 
interface and simple and friendly documentation, and many 
options may be confusing, right?

While R is command line software in nature. My own experience 
was like banging my head all over for more than a year until 
I felt myself familiar enough to not be scared and find ways 
on my own.

Thus it very very short it would be like... make a package 
called EpiInfo that have the strong points of R and the 
strong points of EpiInfo. This would include a GUI for R. 
There are many GUIs for R around for multi and specific 
plataform such as Rcommander, Rpad, JGR, VIM, RkWard, 
SciViews etc http://www.sciviews.org/_rgui/

So ... what would be the advantages for the end user (and also for
developers) worth of such effort?

(1) developing a package would essentially concentrating 
efforts in the analysis tool and very few, if any, effort in 
the the software core. Core team already made a software 
fully compatible with any OS. In very very short it would be 
an Rcommander with menus for the epi packages already 
avaliable (it couldnt be so simple) :)

(2) make a friendly and yet powerfull tool for 
epidemiologists not initiated in R.

(3) As far as know R does not have a data entry tool. Very 
few functions such as data.entry allow to type in data in a 
spreadsheet layout. Nothing similar EpiInfo, EPi6 or EpiData.

In this particular matter (point 3) this package would very 
encouraging for the not initiated to use R.

Of course, I can not speak for the core R team neither for 
the four epi packages developers already available, but if I 
was you I would consider make Rcommander plug-in or a GUI for 
the epi packages as a first step.

Kind regards and good luck,

Abra?o forte e que a for?a esteja com voc?,

Dr. Pedro Emmanuel A. A. do Brasil
Instituto de Pesquisa Cl?nica Evandro Chagas Funda??o Oswaldo 
Cruz Rio de Janeiro - Brasil Av. Brasil 4365 Tel 55 21 3865-9648
email: pedro.brasil at ipec.fiocruz.br
email: emmanuel.brasil at gmail.com

---Apoio aos softwares livres
www.zotero.org - gerenciamento de refer?ncias bibliogr?ficas.
www.broffice.org ou www.openoffice.org - textos, planilhas ou 
apresenta??es.
www.epidata.dk - entrada de dados.
www.r-project.org - an?lise de dados.
www.ubuntu.com - sistema operacional

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R-sig-Epi Digest, Vol 45, Issue 1

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