2010/12/21 Petr PIKAL :
> Hi
>
> r-help-boun...@r-project.org napsal dne 21.12.2010 11:02:07:
>
>> Hello,
>>
>> I am trying to analyze sociological survey data using R. It is often
>> important in survey to calculate both the actual factor sums and
>> percentages (easily done with describe() ), but
Hello,
I am trying to analyze sociological survey data using R. It is often
important in survey to calculate both the actual factor sums and
percentages (easily done with describe() ), but also the numbers and
total percentage of NA's. Often it is important to present NA's in
graphs besides the fa
Hello,
I am trying to analyze sociological survey data using R. It is often
important in survey to calculate both the actual factor sums and
percentages (easily done with describe() ), but also the numbers and
total percentage of NA's. Often it is important to present NA's in
graphs besides the fa
kspace...
Hope this helps
Donatas G.
Horace Tso rašė:
> Thought I should copy the list with Matthieu's response.
>
> H
>
> -Original Message-
> From: Matthieu Stigler [mailto:[EMAIL PROTECTED]
> Sent: Wednesday, November 05, 2008 8:29 PM
> To: Horace Tso; [EMAI
I am looking for simple introduction to cluster analysis using R, that would
be understandable to a novice in statistics. Or, could someone perhaps help
me understand how to proceed in my analysis? I am very new to both statistics
and R, but am trying hard to avoid having to use SPSS as everyone
I have found several resources very helpful:
http://cran.r-project.org/doc/contrib/Paradis-rdebuts_en.pdf
http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/Getting-Started-with-the-Rcmdr.pdf
Donatas
On Tuesday 19 February 2008 15:14:19 jim holtman rašė:
> I have no idea what "numbers form the RAD7 ma
I have been asking these same questions here on this list half a year before.
You will probably find what you need by following this link and the
subsequent discussion:
https://stat.ethz.ch/pipermail/r-help/2007-July/136162.html
Donatas
On Tuesday 19 February 2008 15:14:19 jim holtman rašė:
>
On Wednesday 19 December 2007 14:12:16 rašėte:
> sapply(levels(DATA$know1), function(x)subset(DATA, (know1==x &
> know2==x)), simplify=F)
Hey, thanks, that seems to work!
--
Donatas Glodenis
http://dg.lapas.info
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R-help@r-project.org mailing list
ht
Hi, I have a data frame DATA, which (simplified of course) looks like this:
know1 = c("Y","N","N","Y","N","N","Y","Y","N")
par1=c(1,4,5,3,3,2,3,3,5)
know2 = c("Y","Y","N","Y","N","N","N","Y","Y")
par2=c(3,4,4,3,5,2,4,3,2)
DATA=data.frame(know1,par1,know2,par2)
it represents answers in a questionn
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