Hi, I am trying to use F test or Chi-square test to test if 2 5-parameter (A,
B, xmid, scal and H) logistic curves are parallel based on residual sum of
squares.
What's usually done is to first fit the 2 curves using a constraint (or global)
model where all parameters are kept the same except f
specification? And what
about arguments "lower=" and "upper="? I feel they might be related to
specifying constrained models.
Thanks
John
--- On Sat, 3/13/10, Eik Vettorazzi wrote:
> From: Eik Vettorazzi
> Subject: Re: [R] testing parallelism of does-response curves us
Hi I got an error message using datadist() from Design package:
> library(Design,T)
> dd <- datadist(beta.final)
> options(datadist="dd")
> lrm(Disease ~ gsct+apcct+rarct, x=TRUE, y=TRUE)
Error in eval(expr, envir, enclos) : object "Disease" not found
All variables inclduing response
Hi, another question about validate() in Design library. The arugment "B" of
this function is number of repetition for method="bootstrap", which is easy to
understand; but for method="crossvalidation", B is the number of groups of
omitted observations. This is confusing, I don't understand what
m: Jorge Ivan Velez
> Subject: Re: [R] datadist() in Design library
> To: "array chip"
> Cc: "R mailing list"
> Date: Thursday, July 9, 2009, 6:55 PM
> Dear John,
> Have you tried it specifying the 'data'
> argument as suggested in lrm help?
> Tr
Hi, I am wondering if there is a way to specify the prevalence of events in
logistic regression using lrm() from Design package? Linear Discriminant
Analysis using lda() from MASS library has an argument "prior=" that we can use
to specify the prevalent of events when the actual dataset being a
Hi, I have very simple balanced randomized block design where I total have 48
observations of a measure of weights of a product, the product was manufactured
at 4 sites, so each site has 12 observations. I want to use lme() from nlme
package to estimate the standard error of the product weight.
Thanks Dennis for the thorough explanation and correction on the design.
John
--- On Thu, 4/1/10, Dennis Murphy wrote:
From: Dennis Murphy
Subject: Re: [R] trying to understand lme() results
To: "array chip"
Cc: R-help@r-project.org
Date: Thursday, April 1, 2010, 12:33 AM
Hi:
O
Hi, I encountered a problem of not being able to read in an excel spreadsheet
using read.xls() in the xlsReadWrite package. can anyone help? Here is an
example code
write.xls(matrix(1:9,nrow=3),"ttt.xls")
read.xls("ttt.xls")
Error in read.xls("ttt.xls") :
Unexpected error. Message: Can't fin
Thanks for the link, very useful. A simple fix to the code using
normalizePath(), or full path name.
read.xls(normalizePath("ttt.xls"))
--- On Fri, 4/2/10, Gabor Grothendieck wrote:
> From: Gabor Grothendieck
> Subject: Re: [R] can't read excel file with read.xls()
>
I am working on plotting a response surface using wireframe(). The default
style/orientation is
z
|
|
y |
\ |
\ |
\ |
\|
\ |
\ |
\ |
\|x
0
Now what I want the orientation of axes is:
Thank you David. The document is very helpful.
I had a typo in my 2nd example plot, one of the "z" is "x", "z" is the vertical
one.
Thanks
John
--- On Wed, 4/7/10, David Winsemius wrote:
> From: David Winsemius
> Subject: Re: [R] 3-D response surface
f the plot?
Thanks
John
--- On Wed, 4/7/10, David Winsemius wrote:
> From: David Winsemius
> Subject: Re: [R] 3-D response surface using wireframe()
> To: "array chip"
> Cc: r-help@r-project.org
> Date: Wednesday, April 7, 2010, 8:07 AM
> A search with the following
Scott,
This is a good explanation and a good practice.
Thank you,
John
--- On Thu, 4/8/10, Waichler, Scott R wrote:
> From: Waichler, Scott R
> Subject: Re: 3-D response surface using wireframe()
> To: "arrayprof...@yahoo.com"
> Cc: "r-help@r-project.org"
> Date: Thursday, April 8, 2010, 9
rom: David Winsemius
> Subject: Re: [R] 3-D response surface using wireframe()
> To: "array chip"
> Cc: r-help@r-project.org
> Date: Wednesday, April 7, 2010, 9:22 PM
>
> On Apr 7, 2010, at 8:58 PM, array chip wrote:
>
> > With the help document, i finally fi
D dataset. Hope I have explained
clearly this time.
Many thanks
John
--- On Thu, 4/8/10, David Winsemius wrote:
> From: David Winsemius
> Subject: Re: [R] 3-D response surface using wireframe()
> To: "array chip"
> Cc: r-help@r-project.org
> Date: Thursday, April 8,
axes are draw
)
Thank you all very much for the help. It's fun to learn.
John
--- On Thu, 4/8/10, Felix Andrews wrote:
> From: Felix Andrews
> Subject: Re: [R] 3-D response surface using wireframe()
> To: "David Winsemius"
> Cc: "array chip" , r-help@r-pro
Sorry the example plot didn't go through last time, here it is:
Thanks
John
--- On Fri, 4/9/10, array chip wrote:
> From: array chip
> Subject: Re: [R] 3-D response surface using wireframe()
> To: "David Winsemius" , "Felix Andrews"
>
> Cc: r-he
id Winsemius
> Subject: Re: [R] 3-D response surface using wireframe()
> To: "array chip"
> Cc: r-help@r-project.org
> Date: Friday, April 9, 2010, 3:48 PM
> I do not think the mail server
> accepts .jpg formats which was the
> format in which I got your attachment
Hi, all, I found that the smooth.spline() function produces different results
between R and S-Plus. I was trying to play different parameters of the function
without any success. The script of the function contains Fortran code, so it
seems impossible to port the code from S-Plus to R (or I may
Hi all, I am using nsprcomp() from nsprcomp package to run sparse PCA. The
output is very much like regular PCA by prcomp() in that it provides "sdev" for
standard deviation of principle components (PC).
For regular PCA by prcomp(), we can easily calculate the percent of total
variance explai
HI Christian,
Thanks so much for the detailed explanation! I look forward to the new release
of nsprcomp package! At the meantime, I will use the function below for
calculation of "adjusted" standard deviation. I have 2 more questions, hope you
can shed some lights on:
1). Assume now I can cal
Hi Christian,
Thank you so much for sharing your thoughts, I was a real pleasure to read and
learn! Approximately when do you expect the new release of the package?
Best,
John
From: Christian Sigg
Cc: "r-help@r-project.org"
Sent: Monday, September 9, 20
Hi I have a character matrix with 2 columns A and B, If I want to sort the
matrix based on the column B, but based on a specific order of characters:
mat<-cbind(c('w','x','y','z'),c('a','b','c','d'))
ind<-c('c','b','d','a')
I want "mat" to be sorted by the sequence in "ind":
[,1] [,2]
[1,]
ion of the vector
'ind' and to order that permutation gives its inverse.
mat <- cbind(c('w','x','y','z'),c('a','b','c','d'))
ind <- c('c','b','d','a')
or
Hi James,
I am trying to combine 11 data frames by column, not by row. My original
message has 11 data text files attached, did they go through so you can try my
codes?
Thanks
John
From: J Toll
Cc: "r-help@r-project.org"
Sent: Friday, January 11, 2013
Hi Dennis,
Actually, I am trying to combine them by COLUMN, so
that's why I am using merge(). The first loop was to simply read these
protein data into R as 11 data frames, each data frame is 165 x 2. Then I
use merge() to combine these data frames into 1 big data frame by
column with these in
I just figured out the reason was the column (the 1st column in each data frame
"gene.name") by which to merge each data frame has no unique values, some
values were repeated, so when merging, the data frame gets bigger and bigger
exponentially.
Sorry to bother all.
John
___
Hi, I am new to bioconductor, trying to install KEGGSOAP package, but got
warnings() when installing and error message when trying to load the package,
can anyone suggest what went wrong?
many thanks
John
> source("http://bioconductor.org/biocLite.R";)
Bioconductor version 2.11 (BiocInstalle
Hi, I am wondering how the confidence interval for Kaplan-Meier estimator is
calculated by survfit(). For example,
> summary(survfit(Surv(time,status)~1,data),times=10)
Call: survfit(formula = Surv(rtime10, rstat10) ~ 1, data = mgi)
time n.risk n.event survival std.err lower 95% CI upper 95% C
Hi all, I am new to meta-analysis. Is there any special package that canÂ
calculate "summarized" sensitivity with 95% confidence interval for a
diagnostic test, based on sensitivities from several individual studies?Â
Thanks for any suggestions.
John
From:
Hi all, let's say we can fit a Cox model with a numeric variable "x" as the
independent variable. The we can calculate, say 10-year survival, for any given
value of "x" (0 to 10 in increment of 0.1 in the example below):
> fit <- coxph(Surv(time, event)~x,dat)
> surv10yr<-
summary(survfit(fit,ne
Hi all, let's say we can fit a Cox model with a numeric variable "x" as the
independent variable. The we can calculate, say 10-year survival, for any given
value of "x" (0 to 10 in increment of 0.1 in the example below):
> fit <- coxph(Surv(time, event)~x,dat)
> surv10yr<-
summary(survfit(fit,n
Hi, I am using clogit() from survival package to do conditional logistic
regression. I also need to make prediction on an independent dataset to
calculate predicted probability. Here is an example:
> dat <- data.frame(set=rep(1:50,each=3), status=rep(c(1,0,0),50),
> x1=rnorm(150,5,1), x2=rnorm
Thank you Peter. Any other suggestions are absolutely welcome!!
John
From: peter dalgaard
Cc: "r-help@r-project.org"
Sent: Monday, June 16, 2014 2:22 AM
Subject: Re: [R] prediction based on conditional logistic regression clogit
> Hi, I am using clogit
Hi, can anyone help me to understand the standard errors printed in the output
of survfit.coxph()?
time<-sample(1:15,100,replace=T)
status<-as.numeric(runif(100,0,1)<0.2)
x<-rnorm(100,10,2)
fit<-coxph(Surv(time,status)~x)
### method 1
survfit(fit, newdata=data.frame(time=time,status=status
Thank you Terry for the explanation!
John
From: "Therneau, Terry M., Ph.D."
Sent: Monday, June 30, 2014 6:04 AM
Subject: Re: standard error of survfit.coxph()
1. The computations "behind the scenes" produce the variance of the cumulative
hazard.
This is
Dear Terry,
I was trying to use your explanation of the standard error estimate from
survfit.coxph() to verify the standard error estimates for the method of
log(log(S)), but couldn't get the estimates correct. Here is an example using
the lung dataset:
> fit<-coxph(Surv(time,status)~wt.loss,l
Terry, I figured out that variance of log(-log(S)) should be (1/H^2)var(H), not
(1/S^2)var(H)!
Thanks
John
e...@mayo.edu>; "r-help@r-project.org"
Sent: Monday, July 21, 2014 11:41 AM
Subject: Re: standard error of survfit.coxph()
Dear Terry,
I was try
Dear Terry/All,
I was trying to use your explanation of the standard error estimate from
survfit.coxph() to verify the standard error estimates for the method of
log(log(S)), but couldn't get the estimates correct. Here is an example using
the lung dataset:
> fit<-coxph(Surv(time,status)~wt.
Hi, I am trying to calculate net reclassification improvement (NRI) and
Inegrated Discrimination Improvement (IDI) for a survival dataset to compare 2
risk models. It seems that the improveProb() in Hmisc package does this only
for binary outcome, while rcorrp.cens() does take survival object, b
Hi, I have some questions on how to estimate the survival function from a Cox
model. I know how to do this in R using survfit().
But let's say the model was done is another software, and I was only given the
estimate of baseline cumulative hazard "A0(t=10)" at the specified time "t=10"
(basel
Hi, I have some questions on how to estimate the survival function from a Cox
model. I know how to do this in R using survfit().
But let's say the model was done is another software, and I was only given the
estimate of baseline cumulative hazard "A0(t=10)" at the specified time "t=10"
(basel
Hi, I have some questions on how to estimate the survival function from a Cox
model. I know how to do this in R using survfit().
But let's say the model was done is another software, and I was only given the
estimate of baseline cumulative hazard "A0(t=10)" at the specified time "t=10"
(basel
Hi, I noticed that when I install/update packages, the installation folder is
C:/User/My Document/R, not in C:/Program Files/R. R itself was still in Program
Files folder. Don't know how this has happened. It used to work
ok.Any clues or how to correct the problem is
appreciated!ThanksJohnhttp:
http://overview.mail.yahoo.com?.src=iOS";>Sent from Yahoo
Mail for iPhone
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__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-projec
http://overview.mail.yahoo.com?.src=iOS";>Sent from Yahoo
Mail for iPhone
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__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-projec
Hi, if 50% survival probability horizontal line in a Kaplan-Meier survival
curve overlap one of the step line between 2 time points t1 and t2, the
survfit() from survival package estimates median survival as t2 (the longest
time point). But I saw some articles (page 23:
http://www.amstat.org/ch
Hi, I wanted to remove redundant rows (with same entry in columns) in a data
frame. For example, with this data frame:
> dat<-cbind(x=c('a','a','b','b','c','c'),y=c('x','x','d','s','g','g'))
> dat
x y
[1,] "a" "x"
[2,] "a" "x"
[3,] "b" "d"
[4,] "b" "s"
[5,] "c" "g"
[6,] "c" "g"
after re
sorry.. don't know unique().. such a great function
From: Bert Gunter
Cc: "r-help@r-project.org"
Sent: Tuesday, January 28, 2014 2:21 PM
Subject: Re: [R] unique rows
Inline.
-- Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
"Data i
please ignore. actually the median survival from survfit() is the mean of the 2
time points.
To: R help
Sent: Tuesday, January 28, 2014 11:27 AM
Subject: [R] median survival
Hi, if 50% survival probability horizontal line in a Kaplan-Meier survival
curve
Hi, this is a statistical question rather than a pure R question. I have got
many help from R mailing list in the past, so would like to try here and
appreciate any input:
I conducted Mantel-Haenszel test to show that the performance of a diagnostic
test did not show heterogeneity among 4 study
ate Medical University
Binghamton, NY
array chip wrote:
> Hi, this is a statistical question rather than a pure R question. I have got
> many help from R mailing list in the past, so would like to try here and
> appreciate any input:
>
> I conducted Mantel-Haenszel test to show
Hi, this is not R technical question per se. I know there are many excellent
statisticians in this list, so here my questions: I have dataset with ~1800
observations and 50 independent variables, so there are about 35 samples per
variable. Is it wise to build a stable multiple logistic model wit
stable model, as your dataspace is
> about as sparse as it can get. On top of that, interpreting a model
> with 50 variables is close to impossible, and then I didn't even start
> on interactions. No point in trying I'd say. If you really need all
> that information, you might want
Hi, I am learning xyplot. I have an example dataset attached.
plotdata<-read.table("plotdata.txt",sep='\t',header=T,row.names=1)
head(plotdata,n=4)
y x type
1 -4.309601 -0.7448405A
2 -4.715421 0.7875994A
3 -2.310638 0.5455310A
4 -2.685803 10.4116868A
xyplot(y
ines(x,-1.324+0.1117*x-0.0006357*x*x)
})
type='b' doesn't give me a smooth line, so it didn't produce what I want.
Thanks
John
- Original Message ----
From: Bert Gunter
To: array chip ; r-help@r-project.org
Sent: Thu, July 8, 2010 4:25:51 PM
Subject: RE: [R] xypl
Hi, suppose I have a data frame as below:
dat<-cbind(expand.grid(id=c(1,2,3),time=c(0,3,6),mode=c('R','L'),rep=(1:3)),y=rnorm(54))
I kind of want to "squeeze" the data frame into a new one with averaged "y"
over
"rep" for the same id, time and mode. taking average is easy with tapply:
tapply(
-0.21924078
37 1 0 R 3 1.175192908 -0.21924078
But I only need one row:
id time modeavg.y
110 R-0.21924078
Thanks again,
John
- Original Message
From: David Winsemius
To: array chip
Cc: r-hel
Thank you Peter, yes this is what I need!
John
- Original Message
From: Peter Alspach
To: array chip ; David Winsemius
Cc: "r-help@r-project.org"
Sent: Thu, September 9, 2010 4:26:53 PM
Subject: RE: [R] "sequeeze" a data frame
Tena koe John
?aggregate
may
from the output, I think it's both.
- Original Message
From: John Sorkin
To: r-help@r-project.org
Sent: Fri, September 10, 2010 5:25:44 AM
Subject: [R] lme, groupedData, random intercept and slope
Windows Vista
R 2.10.1
Does the following use of groupedData and lme produce an anal
But as far as I know, profile() seems to be de-activated in the lme4 package.
- Original Message
From: Gavin Simpson
To: John Sorkin
Cc: r-help@r-project.org; Bert Gunter
Sent: Fri, September 10, 2010 2:05:37 AM
Subject: Re: [R] lmer fixed effects, SE, t . . . and p
On Thu, 2010-09-
ckages:
[1] minqa_1.1.9Rcpp_0.8.6 Matrix_0.999375-43 lattice_0.18-8
loaded via a namespace (and not attached):
[1] grid_2.11.1nlme_3.1-96splines_2.11.1 stats4_2.11.1 tools_2.11.1
Any suggestions would be appreciated.
John
- Original Message
From: Ga
estion is more suitable to R-mixed-models, but response there is
pretty slow,..
Thanks,
John
----- Original Message
From: Gavin Simpson
To: array chip
Cc: John Sorkin ; r-help@r-project.org; Bert
Gunter
Sent: Fri, September 10, 2010 10:46:16 AM
Subject: Re: lme4a package loadi
Hi all, I
When I plot both lines and points using type=c('l', 'p') in xyplot(), if I want
to include in legend both of them using keys=list(lines=list(col=1:3),
points=list(pch=1:3)), the lines and points are plotted side by side in legend.
Is there anyway to plot the points in the middle of th
Hi, another question: is there any argument that controls the line width of
axis
box of xyplot()? I tried lwd=2 or lwd.axis=2 in xyplot() or within
scales=list()
argument, without success.
Thanks
John
__
R-help@r-project.org mailing list
https://st
From: David Winsemius
To: array chip
Cc: r-help@r-project.org
Sent: Mon, September 13, 2010 4:05:04 PM
Subject: Re: [R] xyplot legends
On Sep 13, 2010, at 6:25 PM, array chip wrote:
> Hi all, I
>
> When I plot both lines and points using type=c('l', 'p') in xy
From: Daisy Englert Duursma
To: array chip
Cc: r-help@r-project.org
Sent: Mon, September 13, 2010 8:05:53 PM
Subject: Re: [R] xyplot axis line width
check out ?par for all the details on plotting
‘mgp’ The margin line (in ‘mex’ units) for the axis title,
axis labels and axis line. Note that
Thank you Deepayan. This is exactly what I needed.
John
- Original Message
From: Deepayan Sarkar
To: array chip
Cc: r-help@r-project.org
Sent: Tue, September 14, 2010 4:52:29 AM
Subject: Re: [R] xyplot axis line width
On Tue, Sep 14, 2010 at 4:26 AM, array chip wrote:
>
Hi, I asked this on mixed model mailing list, but that list is not very active,
so I'd like to try the general R mailing list. Sorry if anyone receives the
double post.
Hi, I have a dataset of animals receiving some eye treatments. There are 8
treatments, each animal's right and left eye was
t variance estimate (0.01875) is the same
between aov, lmer and lme. But I am not sure how to relate results between aov
and lmer/lme for the other 2 variance components (id and eye%in%id).
Thanks
John
- Original Message
From: Peter Dalgaard
To: array chip
Cc: r-help@r-project.org
Sent
xed models,
are the results from glht() reasonable/meaningful? If not, will the suggested
1-way ANOVA used together with glht() give us correct post-hoc multiple
comparsion results?
Thank you very much!
John
- Original Message
From: Peter Dalgaard
To: array chip
Cc: r-help@r-project.
Thank you Peter and Ben for your comments.
John
- Original Message
From: Peter Dalgaard
To: array chip
Cc: r-help@r-project.org; r-sig-mixed-mod...@r-project.org
Sent: Mon, September 20, 2010 12:28:43 PM
Subject: Re: [R] lmer() vs. lme() gave different variance component estimates
Is there anyway to make plotting point character being thicker in xyplot? I
mean
not larger which can achieved by "cex=2", but thicker. I tried lwd=2, but it
didn't work. I know "lwd" works in regular plot() not only for lines, but also
for points. For example
plot(1:10, lwd=2)
Thanks
John
Thank you Greg. I also got it work by using panel.points (lwd=2) instead of
using panel.xyplot()
- Original Message
From: Greg Snow
To: array chip ; "r-help@r-project.org"
Sent: Thu, September 23, 2010 2:48:06 PM
Subject: RE: [R] how to make point character thicker
x27;,
points=list(col=1:2,pch=0:1,cex=2,lwd=2),
text=list(lab=c('A','B'),cex=1.5,font=2)))
Any suggestions?
Thanks
John
- Original Message
From: array chip
To: Greg Snow
Cc: r-help@r-project.org
Sent: Thu, September 23, 2010 4:03:00 PM
Subject: Re: [R] how to make
Yes, it does what I want. Thank you Peter! Just wondering what else grid.pars
controls? not just the symbol in legend, right?
John
- Original Message
From: Peter Ehlers
To: array chip
Cc: "r-help@r-project.org"
Sent: Thu, September 23, 2010 4:34:44 PM
Subject: Re: [R] h
Hi I am using xyplot() to plot on the log scale by using scale=list(log=T)
argument. For example:
xyplot(1:10~1:10, scales=list(log=T))
But the axis labels are printed as scientific notation (10^0.0, etc), instead
of
fixed notation. How can I change that to fixed notation?
options(scipen=4) d
Thanks for the suggestion. But my example is just an example, I would prefer to
have some generalized solution, like what options(scipen=4) does in general
graphics, which usually gave pretty axis labels as well.
Any suggestions?
Thanks
John
From: Henrique Da
, 4
Error in construct.scales(log = TRUE, labels = list(x = c(0, 0.6931, 1.0986, :
the at and labels components of scales may not be lists when relation = same
Syntax problem in this last command?
Thanks
On 27-Sep-10, at 12:16 PM, Henrique Dallazuanna wrote:
> Try this:
>
> x
ls$at <- log(tick.at, 10)
ans$left$labels$labels <- as.character(tick.at)
ans }
- Original Message ----
From: array chip
To: Don McKenzie ; Henrique Dallazuanna
Cc: R-help Forum
Sent: Mon, September 27, 2010 3:09:20 PM
Subject: Re: [R] scientific vs. fixed notation in xyplot
Thank you Dr. Sarkar. yscale.components.log10.3 is pretty good choice.
John
- Original Message
From: Deepayan Sarkar
To: array chip
Cc: Don McKenzie ; Henrique Dallazuanna
; R-help Forum
Sent: Mon, September 27, 2010 8:07:15 PM
Subject: Re: [R] scientific vs. fixed notation in
Hi, I am wondering if anyone can propose a simple/best way to do the following:
Let's say I have a data frame
dat <-
cbind(expand.grid(mode=c('right','left'),time=0:3,id=c('p1','p2','p3')),y=c(3,5,rep(4,6),6,2,rep(3,6),4,4,rep(2,6)))
dat
mode time id y
1 right0 p1 3
2 left0 p1
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spec...@stat.berkeley.edu
On Fri, 1 Oct 2010, array chip wrote:
> Hi, I am wondering if anyone can propose a simple/be
Hi, is there a way to retrieve the extremes of the user coordinates of the
plotting region, like what par("usr") does in general graphics? I'd like to use
them to print additional texts at certain place inside each panel. Thanks
John
[[alternative HTML version deleted]]
__
Hi, how can I make the point characters thicker (NOT larger) in xyplot when
groups= argument is used?
dat<-data.frame(x=1:100,y=1:100,group=rep(LETTERS[1:5],each=20))
### lwd=2 doesn't work here
xyplot(y~x,groups=group,data=dat,col=1:4,pch=1:4,lwd=2)
### lwd=2 works with panel.points(),
Hi, is there a package for getting type II or type III tests on mixed models
(lme or lmer), just like what Anova() in car package does for aov, lm, etc.?
Thanks
John
[[alternative HTML version deleted]]
__
R-help@r-project.org mailin
Hi, just a general question: when we do hierarchical clustering, should we
compute the dissimilarity matrix based on scaled dataset or non-scaled dataset?
daisy() in cluster package allow standardizing the variables before calculating
dissimilarity matrix; but dist() doesn't have that option at
Hi, I have a dataset where the response for each person on one of the 2
treatments was a proportion (percentage of certain number of markers being
positive), I also have the number of positive & negative markers available for
each person. what is the best way to analyze this kind of data?
I can
:
glm(log(percentage/(1-percentage))~treatment,data=test)
Thanks
John
From: Ben Bolker
To: r-h...@stat.math.ethz.ch
Sent: Tue, December 21, 2010 5:08:34 AM
Subject: Re: [R] logistic regression or not?
array chip yahoo.com> writes:
[snip]
> I can th
Ben, thanks again.
John
From: Ben Bolker
Cc: r-h...@stat.math.ethz.ch; S Ellison ; peter dalgaard
Sent: Tue, December 21, 2010 9:26:29 AM
Subject: Re: [R] logistic regression or not?
On 10-12-21 12:20 PM, array chip wrote:
> Thank you Ben, Steve and Pe
Hi, I noticed a Rdata size issue that's puzzling to me. Attached find 2 example
datasets in text file. Both are 100x5, so the sizes for both text file are the
same. However, when I read them into R, the sizes are much different:
tt<-as.matrix(read.table("tt.txt",header=T,row.names=1))
save(tt,fi
Hi, I am seeking help on designing an algorithm to identify the locations of
stretches of 1s in a vector of 0s and 1s. Below is an simple example:
> dat<-as.data.frame(cbind(a=c(F,F,T,T,T,T,F,F,T,T,F,T,T,T,T,F,F,F,F,T)
,b=c(4,12,13,16,18,20,28,30,34,46,47,49,61,73,77,84,87,90,95,97)))
> dat
97 971
John
From: "ted.hard...@wlandres.net"
Cc: r-h...@stat.math.ethz.ch
Sent: Thu, January 6, 2011 2:57:47 PM
Subject: RE: [R] algorithm help
On 06-Jan-11 22:16:38, array chip wrote:
> Hi, I am seeking help on designing an algorithm to identify the
>
boun...@r-project.org] On Behalf Of array chip
> Sent: Thursday, January 06, 2011 3:29 PM
> To: ted.hard...@wlandres.net
> Cc: r-h...@stat.math.ethz.ch
> Subject: Re: [R] algorithm help
>
[[elided Yahoo spam]]
>
> I made a routine to do this:
>
> f.fragment<-function(a,
Hi, I am wondering if there is a similar effects package for mixed models, just
like what effects package does for linear, generalized linear models?
Specifically I am looking for a way to calculate the SAS-co-called least
squared
means (LS means) in mixed models (I understand there is a substa
Hi, assume that I have a repeated measure dataset with 3 time points: baseline,
day 5 and day 10. There are 4 treatment groups (vehicle, treatment 1, treatment
2 and treatment 3). 20 subjects per treatment group. A simple straight-forward
way to analyze the data is to use mixed model:
model 1:
Hi, I am using read.ssd() from foreign package to read some SAS datasets. I
have
2 types of SAS datasets, one with "sas7bdat" extension, the other with "ssd01"
extension. I have no problem with the first dataset type, but got the following
error message with the 2nd dataset type (with "ssd01" e
Looks like the log file is not appropriately attached. Here it is again. Thanks
for any suggestions.
John
- Original Message
From: array chip
To: r-help@r-project.org
Sent: Mon, August 2, 2010 2:18:32 PM
Subject: [R] read SAS dataset using read.ssd()
Hi, I am using read.ssd() from
HI, I was trying to install xlsx package for reading in Excel 2007 files. The
installation went smoothly. But when I tried to load the library, I got the
following error message:
> library(xlsx)
Loading required package: xlsxjars
Loading required package: rJava
Error : .onLoad failed in loadName
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