paste("A", format(m, scientific=FALSE, trim=TRUE), "B", sep="")
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Daren Tan
Sent: Thursday, July 24, 2008 5:47 PM
To: [EMAIL PROTECTED]
Subject: [R] How to preserve the numeric format and digits ?
Instead of
You might look at the summary method in Dr. Harrell's Hmisc package, I believe
this would give you almost exactly what you want.
latex(summary(gender ~ age + bmi, data=yourdata, method='reverse'))
This will get you quartiles, but if you read the documentation
(?summary.formula) you can see how
Dr. Harrell's Hmisc package has labcurve.
--Matt
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Ted Harding
Sent: Wednesday, July 16, 2008 1:17 PM
To: [EMAIL PROTECTED]
Subject: [R] Labelling curves on graphs
Hi Folks,
I'd be grateful for good suggestio
Apologies, the second method should have been
allCoefs <- vector("list", length(allFits))
for(i in 1:length(allFits)) allCoefs[[i]] <- coef(allFits[[i]])
--Matt
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Austin, Matt
Sent: T
IL PROTECTED]
Sent: Wednesday, June 04, 2008 9:12 PM
To: Austin, Matt
Cc: r-help@r-project.org
Subject: Re: [R] linear model in the repeated data type~
hi:lot thanks,how to use list to extract,I type allFit$coefficents,it came to
nothing,
such as I need to extract the estimates,how to do it by using
How about
library(nlme)
allFits <- lmList(y ~ t|id, data=table1, pool=FALSE)
or
allFits <- by(table1, table1$id, function(x) lm(y ~ t, data=x))
Both ways store the results as a list, so you can access individual results
using list extraction.
--Matt
-Original Message-
From: [EMAIL
There is a R companion to Agresti's text at the following site, I believe the
answer to your question is there:
http://www.stat.ufl.edu/~aa/cda/cda.html
--Matt
Matt Austin
Biostatistics Director
Amgen, Inc
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Beha
I don't believe basehaz takes a newdata argument.
> args(basehaz)
function (fit, centered = TRUE)
NULL
It simply extracts info from the fitted object. I think you want to use
survfit method for coxph objects and then derive/extract what you need.
--Matt
Matt Austin
Global Statistical Leader,
> format(10, big.mark=",", scientific=FALSE)
[1] "1,000,000,000"
--Matt
Matt Austin
Biostatistics Director
Amgen, Inc
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of tom soyer
Sent: Friday, April 04, 2008 2:41 PM
To: r-help@r-project.org
Subject
I find them helpful for displaying the differences in coupled biomarkers
between therapies with different therapeutic targets. You can quickly
see/show which marker is affected quicker and then the other compensating in
response and how they can be reversed depending on target. Having each
measure
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