sarah hoffmann outlook.com> writes:
> I am using lme4 to fit a mixed effects model to my data. I have a
> significant interaction between two variables. My question is what
> is the correct way to get p-values for single terms involved in that
> interaction. I have been using stepwise backwards
Hi
I think I asked the wrong question. Apologies.
Actually I want all the GO BP annotations for my organism and from them I
want to retain only those annotations which annotate less than a specified
number of genes. (say <1000 genes)
I hope I have put it clearly.
sorry again.
Thanks!
On Sun,
Hi,
I am not sure how your dataset looks like. If it is like the one below:
(otherwise, please provide a reproducible example using ?dput())
dat1<- read.table(text="
datetime
10/02/2010
02:30
11/02/2010
04:00
14/02/2010
06:30
",sep="",header=TRUE,stringsAsFactors=FALSE)
lst1<-split(dat1,(seq_al
I think this is much better posted on r-sig-mixed-models rather than r-help.
-- Bert
On Sun, Jul 7, 2013 at 1:14 PM, Stefan Th. Gries wrote:
> Hi all
>
> I have a hopefully not too stupid question about multi-level /
> mixed-effects modeling. I was trying to test a strategy from Crawley's
> 2013
Hi all
I have a hopefully not too stupid question about multi-level /
mixed-effects modeling. I was trying to test a strategy from Crawley's
2013 R Book on a data set with the following structure:
- dependent variable: CONSTRUCTION (a factor with 2 levels)
- independent fixed effect: LENGTH (an i
> x.lab <- gsub(",","*symbol(\"54\")*", x.lab)
Wouldn't using just
"*\",\"*"
instead of
"*symbol(\"54\")*"
as the replacement do the same thing?
To me it is simpler to understand.
Note that this fails if the comma is the first or last
character in the input because '*something*' is
Hello all,
I have posted a reply to Mark and Jeff out of my own fault sent it to them
personally and not the group.
I will re-post the question and Mark's answer so that the community can benefit
from his comments.
It seems that my posts are not in accordance with the guidelines and I will try
Hi,
You could also try ?data.table()
x<- read.table(text="a b c
1 2 3
3 3 4
2 4 5
1 3 4
",sep="",header=TRUE)
library(data.table)
xt<- data.table(xt)
setkey(xt,a)
subset(xt,b==3)
# a b c
#1: 1 3 4
#2: 3 3 4
iord <- order(x$a)
subset(x[iord, ], b == 3)
# a
In Bioconductor, install the annotation package
http://bioconductor.org/packages/release/BiocViews.html#___AnnotationData
corresponding to your chip, e.g.,
source("http://bioconductor.org/biocLite.R";)
biocLite("hgu95av2.db")
then load it and select the GO terms corresponding to your prob
On 07/07/13 22:12, catalin roibu wrote:
Dear R users,
Is there a possibility to extract only the r, CI's envelope and L function
from the output of spatstat?
I use this code
E <- alltypes(df1, Kest, nsim = 100, envelope =
TRUE,savepatterns=TRUE,correction="isotropic")
And second question, is ther
Dear R users,
Is there a possibility to extract only the r, CI's envelope and L function
from the output of spatstat?
I use this code
E <- alltypes(df1, Kest, nsim = 100, envelope =
TRUE,savepatterns=TRUE,correction="isotropic")
And second question, is there a possibility to modify the margin of pl
Hello,
Your question is not very clear, maybe if you post a data example.
To do so, use ?dput. If your data frame is named 'dat', use the following.
dput(head(dat, 50)) # paste the output of this in a post
If you want to get the rownames matching a certain pattern, maybe
something like the f
On 06/07/2013 23:01, Rolf Turner wrote:
On 06/07/13 01:35, Yasmine Refai wrote:
Hello,
When I run the below syntax:
*Trial<-read.table("Trial.txt",header=TRUE)*
*Trial*
*save.image(file="Trial.RData")*
*load("Trial.RData")
fit<-logistf(data=Trial, y~x1+x2)
summary(fit)
AIC(fit)*
I am getting t
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