Hi All,
Thanks for you help, I have loaded the library MASS to call the mca. But when I
want to do the mca, there is another problem, for example
> leaf <- read.table("C:/Documents and Settings/wxh-c/×ÀÃæ/1.txt",
+ col.names=c("size","texture"),header=TRUE)
> leaf
size textur
On Sat, 2004-12-18 at 20:54 -0600, Shawn Way wrote:
> I've seen multiple comments about MS Excel's precision and accuracy.
> Can you please point me in the right direction in locating information
> about these?
>
> Thank you very much,
There was an exchange on this last year and I posted some lin
Shawn Way wrote:
I've seen multiple comments about MS Excel's precision and accuracy.
Can you please point me in the right direction in locating information
about these?
As always, Google is your friend, but see for example
http://www.nwpho.org.uk/sadb/Poisson%20CI%20in%20spreadsheets.pdf
Tim
I've seen multiple comments about MS Excel's precision and accuracy.
Can you please point me in the right direction in locating information
about these?
Thank you very much,
Shawn Way, PE
Engineering Manager
Tanox, Inc.
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED]
Henric Nilsson wrote:
Frank E Harrell Jr said the following on 2004-12-18 15:03:
That is not clear.
Perhaps. And I think this is the issue. From the clients' perspective,
not a single FDA document states that you can use other software than
SAS. They haven't really thought about the fact that th
Hello R users,
I am trying to run a three factor ANOVA on a data set with unequal
sample sizes.
I fit the data to a 'lm' object and used the Anova function from the
'car' package with the 'type=III' option to get type III sums of
squares. I also set the contrast coding option to 'options(contr
Helmut Kudrnovsky web.de> writes:
:
: dear R-friends,
:
: i`ve got a large dataset of vegetation-samples with about 500
: variables(=species) in the following format:
:
: 1 spec1
: 1 spec23
: 1 spec54
: 1 spec63
: 2 spec1
: 2 spec2
: 2 spec253
: 2 spec300
: 2 spec423
: 3 spec20
: 3 spec88
:
Hello,
I am using SVM under e1071 package for nu-regression with 18 parameters. The
variables are ordered factors, factors, date or numeric datatypes. I use the
linear kernel.
It gives the following error that I cannot solve. I tryed debug, browser and
all that stuff, but no way.
The error is:
Frank E Harrell Jr wrote:
... much discussion deleted ...
Regarding CDISC, the SAS transport format that is now accepted by FDA is
deficient because there is no place for certain metadata (e.g., units of
measurement, value labels are remote from the datasets, variable names
are truncated to 8 ch
There were two earlier threads on this topic:
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/17554.html
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/10706.html
Jon
--
Jonathan Baron, Professor of Psychology, University of Pennsylvania
Home page: http://www.sas.upenn.edu/~baron
R search page
Frank E Harrell Jr said the following on 2004-12-18 15:03:
That is not clear.
Perhaps. And I think this is the issue. From the clients' perspective,
not a single FDA document states that you can use other software than
SAS. They haven't really thought about the fact that there isn't any FDA
docu
Helmut Kudrnovsky <[EMAIL PROTECTED]> writes:
> dear R-friends,
>
> i`ve got a large dataset of vegetation-samples with about 500
> variables(=species) in the following format:
>
> 1 spec1
> 1 spec23
> 1 spec54
> 1 spec63
> 2 spec1
> 2 spec2
> 2 spec253
> 2 spec300
> 2 spec423
> 3 spec20
> 3 sp
Henric Nilsson wrote:
Marc Schwartz said the following on 2004-12-18 01:19:
As you are likely aware, other statistically relevant issues are
contained in various ICH guidance documents regarding GCP considerations
and principles for clinical trials:
http://www.ich.org/[EMAIL PROTECTED]&@_TEMPLATE=2
Dear Helmut,
How about table(species, sample)?
Regards,
John
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario
Canada L8S 4M4
905-525-9140x23604
http://socserv.mcmaster.ca/jfox
> -Original Message-
Helmut Kudrnovsky wrote:
dear R-friends,
i`ve got a large dataset of vegetation-samples with about 500
variables(=species) in the following format:
1 spec1
1 spec23
1 spec54
1 spec63
2 spec1
2 spec2
2 spec253
2 spec300
2 spec423
3 spec20
3 spec88
3 spec121
3 spec200
3 spec450
.
.
this means: sa
Marc Schwartz wrote:
On Fri, 2004-12-17 at 17:11 -0500, Alexander C Cambon wrote:
I apologize for adding this so late to the "SAS or R software "
thread.
This is a question, not a reply, but it seems to me to fit in well
with
the subject of this thread.
I would like to know anyone's experiences i
dear R-friends,
i`ve got a large dataset of vegetation-samples with about 500
variables(=species) in the following format:
1 spec1
1 spec23
1 spec54
1 spec63
2 spec1
2 spec2
2 spec253
2 spec300
2 spec423
3 spec20
3 spec88
3 spec121
3 spec200
3 spec450
.
.
this means: sample 1 (grassland) with t
Can't you turn the lists into data frames issue unique and
force them back to lists. Here's the code:
L <- list(c("a1","a3","a4"), c("a1","a4","a5"), c("a1","a5","a6"))
M <- list(c("a1","a3","a4"), c("a2","a4","a5"), c("a1","a5","a6"), c("a7",
"a1", "a4"))
LL <- as.data.frame(I(L))
MM <- as.data
Marc Schwartz said the following on 2004-12-18 01:19:
As you are likely aware, other statistically relevant issues are
contained in various ICH guidance documents regarding GCP considerations
and principles for clinical trials:
http://www.ich.org/[EMAIL PROTECTED]&@_TEMPLATE=272
ICH E9 states that
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