Dear R-Community!
The example oats in MASS (2nd edition, 10.3, p.309) is calculated for aov and
lme without interaction term and the results are the same.
But I have problems to reproduce the example aov with interaction in MASS
(10.2, p.301) with lme. Here the script:
library(MASS)
Dear R-Community!
For example I have a study with 4 treatment groups (10 subjects per group) and
4 visits. Additionally, the gender is taken into account. I think - and hope
this is a goog idea (!) - this data can be analysed using lme as below.
In a balanced design everything is fine, but in
Harrell Jr [EMAIL PROTECTED]
An: Karl Knoblick [EMAIL PROTECTED]
CC: r-help@stat.math.ethz.ch
Gesendet: Donnerstag, den 17. Mai 2007, 14:29:08 Uhr
Betreff: Re: [R] How to analyse simple study: Placebo-controlled (2 groups)
repeated measurements (ANOVA, ANCOA???)
Karl Knoblick wrote:
Hallo!
I
Hallo!
I have two groups (placebo/verum), every subject is measured at 5 times, the
first time t0 is the baseline measurement, t1 to t4 are the measurements after
applying the medication (placebo or verum). The question is, if there is a
significant difference in the two groups and how large
Dear Harold,
Thanks! I searched for Hoyt's Anova in R - but without success. Do you know if
there is something available in R?
Karl
- Ursprüngliche Mail
Von: Doran, Harold [EMAIL PROTECTED]
An: Karl Knoblick [EMAIL PROTECTED]; r-help@stat.math.ethz.ch
Gesendet: Dienstag, den 16. Mai
: Tue, 16 May 2006 10:09:54 + (GMT)
From: Karl Knoblick [EMAIL PROTECTED]
Subject: [R] Interrater and intrarater variability (intraclass
correlationcoefficients)
To: r-help@stat.math.ethz.ch
Message-ID: [EMAIL PROTECTED]
Content-Type: text/plain; charset=us-ascii
Hello!
I want to calculate
Hello!
I want to calculate the intra- and interrater reliability of my study. The
design is very simple, 5 raters rated a diagnostic score 3 times for 19
patients.
Are there methods/funtions in R? I only found packages to calculate interrater
variability and intraclass correlation
Thanks! But I could not find a corresponding example in the mentioned book - at
least the calculation of the intra- and interrater variability or the
corresponding intraclass coefficients.
Karl
- Ursprüngliche Mail
Von: Andrew Robinson [EMAIL PROTECTED]
An: Karl Knoblick [EMAIL
- Ursprüngliche Mail
Von: John Fox [EMAIL PROTECTED]
An: Andrew Robinson [EMAIL PROTECTED]; Karl Knoblick [EMAIL PROTECTED]
CC: r-help@stat.math.ethz.ch
Gesendet: Dienstag, den 16. Mai 2006, 15:02:15 Uhr
Betreff: Re: [R] Interrater and intrarater variability (intraclass correlation
Googling shows an pdf - but this link is broken.
Karl
--- Uwe Ligges [EMAIL PROTECTED]
wrote:
Karl Knoblick wrote:
Hallo!
I want to use the package bayesmix. Trying the
examples I had no success. The reason is, I think:
haveJAGS()
[1] FALSE
Have read of JAGS
Sorry about the further question:
I downloaded bayesmix_0.5-3.zip (see below) - but
there is no jags.exe (even no *.exe) included.
Adress:
http://www.ci.tuwien.ac.at/~gruen/BayesMix/
Downloaded:
Windows binaries including JAGS executable:
bayesmix_0.5-3.zip
Karl
Hallo!
I want to use the package bayesmix. Trying the
examples I had no success. The reason is, I think:
haveJAGS()
[1] FALSE
Have read of JAGS executable (I could not find
JAGS.exe in my R directory). What is JAGS? Where can I
find or download it?
Karl
Hello!
merge(TablePatient, TableSpecial, by.x=ID,
by.y=PATIENTID)
works fine for me. (There is also a variable ID in
TableSpecial).
One problem - or what has to be known - is that merge
is using the levels, not the labels, if the merged
variables are factors.
Karl
Hallo!
I read SPSS data in the following way:
library(Hmisc)
library(foreign)
dat-spss.get(surv_abb.sav)
In R1.9.1 I got the message:
Error in all(arg == choices) : Object typeDate not
found
In R1.8.0 the same script works fine.
Does anybody know a possibilty to read a SPSS file
under R1.9.1?
Hi!
Have you downloaded the package multilevel first?
Best wishes,
Karl
___
Bestellen Sie Y! DSL und erhalten Sie die AVM FritzBox SL für 0.
Sie sparen 119 und bekommen 2 Monate Grundgebührbefreiung.
Hallo!
I have a problem with fitting data with nls. The first
example with y1 (data frame df1) shows an error, the
second works fine.
Is there a possibility to get a fit (e.g. JMP can fit
also data I can not manage to fit with R). Sometimes I
also got an error singularity with starting
Try
print(bwplot(...YOUR PARAMETERS...))
Best wishes,
Karl
Dear List members,
I am trying to produce some trellis graphics and to
save them in a
postscript file but I only get blank files. R
behaviour is certainly
strange because I use a loop to generate the
graphics (see code
Hallo!
I want to fit a function. The function is e.g.:
y = c+m1*x if x0, c+m2*x if x=0
where m1, m2 and c is a parameter and x, y are
variables of a data frame.
I think using nls is appropriate. But I do not know,
how to type this formula in nls. Can anybody help?
(If there is a possibility to
Hallo!
I want to understand / recalculate what is done to get
the CI of the logistic regression evaluated with lrm.
As far as I came back, my problem is the
variance-covariance matrix fit$var of the fit
(fit-lrm(...), fit$var). Here what I found and where
I stucked:
-
Hallo!
I want to plot multiple grouped data in a postscript
file using a loop. As I use a loop no plot (or just
one empty plot) is generated. Here an example:
library(nlme)
data(Loblolly) # example data from nlme
postscript(PSFile.ps)
for (i in 1:1) # just as example
{
plot(Loblolly)
}
Thanks, but it does NOT work using a loop (your
example without loop works):
trellis.device(postscript, file = PSFile.ps)
for (i in 1:1)
{
plot(Loblolly)
}
dev.off()
Just an empty postscript file.
Karl.
--- Uwe Ligges [EMAIL PROTECTED] :
Note that this is a lattice plot:
My problem was solved by using
trellis.device(win.metafile,file=Loblolly.wmf,
color=F)
instead of win.metafile(Loblolly.wmf).
(other answers helped also)
(What I found for getting similiar plots as postscript
was color=F in the trellis.device(...) command)
Thanks to all!
Karl.
BTW
Hallo!
I want to plot grouped data in a wmf-file. The
following example gives an error:
library(lattice)
library(nlme)
data(Loblolly) # example data from nlme
win.metafile(Loblolly.wmf)
plot(Loblolly)
dev.off()
After the plot(Loblolly) the following error occurs:
Error in get(x, envir, mode,
Hallo!
GENERAL QUESTION:
I'm trying to change the tick marks of the x-axis in a
grouped data plot (nlme).
CONCRETE EXAMPLE:
In the example (see below) I want the x-axis to have
tick marks at 0, 6, 12, 18, 24. How can I do this?
WHAT I TRIED
I tried normal methods like axis(...) but this does
Hallo!
Does anybody know how to do a forward stepwise
LOGISTIC regression?
(I found lrm(), fastbw() and validate() in the Design
package concerning backward logistic regression - but
no forward)
Thanks!
Karl
__
[EMAIL PROTECTED] mailing list
Hi!
I'm no guru in R. But I can think of 2 ways (have to
be tried):
1) As Uwe Ligges said: just save return the stored
variable a-preprocess(xdata) and return it (if you
want to return more than 1 item use list) and give
this variable to the next function. Example:
func1-function(x)
{
y-x^2
#
because I can not manage it to
reproduce text book examples (see my posting [R] lme:
reproducing example Karl Knoblick (Tue 02 Dec 2003 -
21:34:54 EST)).
Here some sample data:
# Data
# 35 subjects
ID-factor(rep(1:35,each=3))
TREAT-factor(c(rep(A, 60), rep(B, 45)))
TIME-factor(rep(1:3, 35
: Karl Knoblick wrote:
Dear R-community!
I still have the problem reproducing the following
example using lme.
id-factor(rep(rep(1:5,rep(3,5)),3))
factA - factor(rep(c(a1,a2,a3),rep(15,3)))
factB - factor(rep(c(B1,B2,B3),15))
Y-numeric(length=45)
Y[ 1: 9]-c(56,52,48,57,54,46,55,51,51
Dear R-community!
I still have the problem reproducing the following
example using lme.
id-factor(rep(rep(1:5,rep(3,5)),3))
factA - factor(rep(c(a1,a2,a3),rep(15,3)))
factB - factor(rep(c(B1,B2,B3),15))
Y-numeric(length=45)
Y[ 1: 9]-c(56,52,48,57,54,46,55,51,51)
Hi
I searched in the list and only found questions
without answers e.g.
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/19955.html
: Is there a way to get the same results with lme as
with aov with Error()?
Can anybody reproduce the following results with lme:
, Karl Knoblick wrote:
I searched in the list and only found questions
without answers e.g.
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/19955.html
: Is there a way to get the same results with lme
as
with aov with Error()?
Can anybody reproduce the following results with
lme
Hallo!
I have data of the following design:
NSubj were measured at Baseline (visit 1) and at 3
following time points (visit 2, visit 3, visit 4).
There is or is not a treatment.
Most interesting is the question if there is a
difference in treatment between the results of visit 4
and baseline.
32 matches
Mail list logo
