So it was simple, or so it seemed.
Now to throw a spanner in the works!
I got this error when testing it on my more powerful desktop (using one of
my lists put in to a new object) :
#put list in to new object called "temp"
temp<-rg.lmer
#save
save(temp,file="C:\\Users\\...\\R & Data\\rg.lmer.txt
Hi,
I think this is probably (& hopefully) very easy but I the ideas I have
tried don't work.
Simply, I have 2 very large lists in my workspace which take an awfully long
time to make, each containing the information from 12500+ lmer models.
I would like to now save these lists as files (txt, csv.
got it... another merge did the trick
narrow6<-merge(narrow2,narrow5,by=c("gene","gender"))
Thanks for the help Rui
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Thanks,
in a way this has worked... with a slight modification to this:
narrow3<-aggregate(narrow2$value~narrow2$gene+narrow2$gender,data=narrow2,mean)
narrow4<-aggregate(narrow2$value~narrow2$gene+narrow2$gender,data=narrow2,sd)
which gives a table of the 24000 gene&gender means (narro
Hi
I think/hope there will be a simple solution to this but google-ing has
provided no answers (probably not using the right words)
I have a long data frame of >2 000 000 rows, and 6 columns. Across this
there are 24 000 combinations of gene in a column (n=12000) and gender in a
column (n=2... obv
Well, I'm going to reply to my own thread with a solution here, turns out
one attempt we made last week nearly had it, slight adjustment made it work.
For anyone that is interested / in the future wants to achieve the same
thing >
*varcomp <- matrix(nrow=0, ncol=3)
for (i in 1:nlevels(na
Hi,
I'm still having problems putting the variance components of my model in to
a data frame, it is a continuation of this discussion,
http://r.789695.n4.nabble.com/ANOVA-problem-td4609062.html, but now focussed
on the problem of extracting variance components. I have got my mixed
effects model now
,2,1,2,1,2,1,2,1,2))
df$V<-as.numeric(c(1,2,12,21,5,6,12,34,1,6,52,41,5,43,13,24))
It is worth noting the actual data this will be used on is >1*G's,
2*S's, 40*L's, and 2*R's so hand writing an ANOVA for each G is not
preferred...
Here is a twitter link to a
coxph.html)
arguments but I can't seem to get them to work, maybe it's because its a
monday night, but I seem to have hit a dead end... bad times.
robgriffin247 wrote
>
> Hi David thanks for the help, i was just looking back to say I have found
> my solution (i think) and as you
Hi David thanks for the help, i was just looking back to say I have found my
solution (i think) and as you suggested survfit was the way to go.
my solution was this:
model<-survfit(Surv(a$longevity)~a$sex)
plot(model,ylab="proportion alive",xlab="time (days)",col=c("red","blue"))
--
View this mes
Hello
I'm trying to make survival curves for some longevity data -
100 males and 100 females, some of which are still living (not dead at the
end of survey)
I would like to make sex specific survival curves as time on the X axis,
proportion alive on the Y, and a line for each sex (two lines)
Dat
Hello,
I have a large data set which I am trying to get in to a long/narrow format.
I have given an example below of how I want my data to look before and
after... any ideas for an easy way to do this?
*###Start With this...
*set.seed(1)
a=rnorm(10)
b=rnorm(10)
c=rnorm(10)
d=rnorm(10)
e=rnorm(10)
Hi,
I am trying to put larger axis labels on my graphs (using cex.axis and
cex.label) but when I do this the top of the text on the Y axis goes outside
of the window which you can see in this picture
-http://twitter.com/#!/robgriffin247/status/142642881436450816/photo/1 - (if
you click on the
Just as an update on this problem:
I have managed to get the variance for the selected columns
Now all I need is the covariance between these 2 selections -
the two target columns are and the aim is that a new column contain a
covariance value between these on each row:
maindata[,c(174:213)] an
*The situation (or an example at least!)*
example<-data.frame(rep(letters[1:10]))
colnames(example)[1]<-("Letters")
example$numb1<-rnorm(10,1,1)
example$numb2<-rnorm(10,1,1)
example$numb3<-rnorm(10,1,1)
example$id<-c("CG234","CG232","CG441","CG128","CG125","CG182","CG232","CG441","CG232","CG125")
data$C <- pmax(data$A,data$B)
worked perfectly thank you very much
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Hi,
I'm sure there is a pretty simple answer to this but I have had my head
buried in the R book and on help pages for a while now and I've not made any
progress.
In simple terms:
I have 2 columns of data, column A and column B. I want to create a new
column (C) and fill it with the largest value
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