Displaying 8 results from an estimated 8 matches for "szlevin".
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szlevine
2005 Nov 24
4
Survreg Weibull lambda and p
Hi All,
I have conducted the following survival analysis which appears to be OK
(thanks BRipley for solving my earlier problem).
> surv.mod1 <- survreg( Surv(timep1, relall6)~randgrpc, data=Dataset,
dist="weibull", scale = 1)
> summary(surv.mod1)
Call:
survreg(formula = Surv(timep1, relall6) ~ randgrpc, data = Dataset,
dist = "weibull", scale = 1)
2005 Jun 26
4
Mixed model
Hi All,
I am currently conducting a mixed model. I have 7 repeated measures on a
simulated clinical trial. If I understand the model correctly, the
outcome is the measure (as a factor) the predictors are clinical group
and trial (1-7). The fixed factors are the measure and group. The random
factors are the intercept and id and group.
I tried using 2 functions to calculate mixed effects.
2006 Jan 02
1
ARIMA?
Hi All.,
Following on from all the help I received earlier ..
Just so as you know a well known text book (T&F) uses "repeated
observations"
- I think perhaps they meant repeated measures in retrospect
I am a total beginer to ARIMA, but have read a a basic text.
I read that ARIMA requires a minimum of 50 repeated measures in time
(repeated measures)-
Unfortunately, I have 8
2006 Jan 23
1
Trees
Hi.,
I would like to conduct a CHAID tree analysis - Chi-square Automatic
Interaction Detector.
>From what I can make out from MASS, tree, rpart, and a quick search it
isn't available
as a package.
Is that correct or have I missed it? Has anyone an available
implementation of it?
Thanks
Stephen
Nana Mail <http://mail.nana.co.il> - Get Your Free Personal Outlook 2003
Now
2006 Mar 12
1
meta / lme
Hi
I'm conducing a meta-analysis using the meta package.
Here's a bit of code that works fine -
tmp <- metacont(samplesize.2, pctdropout.2, sddropout.2,
samplesize.1, pctdropout.1, sddropout.1,
data=Dataset, sm="WMD")
I would now like to control for a couple of variables (continuous and
categorical) that aren't in the equation.
Is meta
2006 Jan 16
1
gplots
Hi
I am sure that this question has been asked before ... appologies in
advance
This - which comes out very nicely - better than the commercial stuff.
plotmeans (cdpy~Dodefordpy, Data = Dataset, connect = False, minbar = 1,
mean.labels = FALSE, col = "blue", barwidth = 1.5, barcol = "red",
ci.label = FALSE, xlab="Onset", pch = 15, par(las =2)).
Only one snag I
2005 Jul 18
1
Survival dummy variables and some questions
Hi All,
I am currently conducting some survival analyses. I would like to
extract coefficients at each level of the IVs.
I read on a previous posting that dummy regression using coxph was not
possible.
Therefore I though, hey why not categorize the variables
(I realize some folks object to categorization but the paper I am
replicating appears to have done so ...)
and turn the variables
2005 Nov 22
3
Weibull and survival
Hi
I have been asked to provide Weibull parameters from a paper using
Kaplan Meir survival analysis.
This is something I am not familiar with.
The survival analysis in R works nicely and is the same as commercial
software (only the graphs are superior in R).
The Weibull does not and produces an error (see below).
Any ideas why this error should occur?
My approach may be spurious.