RE: forest plots in Xpose?
Dear all,
Folks at Metrum published some R-code on how to generate these kind of
covariate plots, including uncertainty of the effect size from a bootstrap:
http://metrumrg.googlecode.com/svn/trunk/inst/example/project/script/covplot.pdf
Here is also a very nice presentation from Marc Gastonguay about this topic:
http://metrumrg.com/assets/pubs/GastonguayPAGE2011.pdf
Regards, Andreas.
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Ron Keizer
Sent: Thursday, September 17, 2015 02:09
To: Pascal Girard <[email protected]>
Cc: [email protected]
Subject: Re: [NMusers] forest plots in Xpose?
dear Pascal,
there seem to be copies of that library e.g. here
( http://www2.uaem.mx/r-mirror/web/packages/popPK/index.html) and here
( https://cran.r-project.org/src/contrib/Archive/popPK/). You should be able to
download from there and install from the local zip file. I don't know this
library, so I'm not sure if it still works with current version of Xpose. I
also don't know of a different module that creates these plots, but with the
dplyr and ggplot2 libraries it shouldn't be more than 5-10 lines of code to
create such a plot.
On a sidenote, I'm not a fan of the term "Forest plot" for these plots. The
"original" Forest plots show data across multiple studies (e.g. in a
meta-analysis), so calling it "Forest plot" could lead to confusion with
statisticians or clinicians. A more important reason, however, is that it is
not immediately clear what is actually shown in the plot. Various covariate
data can be summarized using the "Forest plot style", such as:
- uncertainty in covariate effect size (e.g. obtained from covariance step,
bootstrap, or posterior distribution from MCMC)
- inter-individual variability in covariate effect (distribution of observed
covariate values * covariate effect size)
- time-variance of the covariate effects
- a combination of 1 and 2?
So a covariate "Forest" covariate-plot should always be accompanied with a
description of what data is actually shown.
BTW, I think all of the above plots have utility in some way, either in
diagnosis, data checkout, or communicating modeling results. Would be great if
someone implemented an R package that could do all of the above :) I assume the
popPK package makes type 2, but it is not mentioned in the manual.
best regards,
Ron
On Wed, Sep 16, 2015 at 12:57 AM, Pascal Girard
<[email protected]<mailto:[email protected]>> wrote:
Dear NONMEM users, Dear Uppsala Folks, Dear Christopher
I was looking for some Xpose function that would automatically create a forest
plot from NONMEM output in order to present the results of covariate analysis,
assuming that all covariate models have been implemented the same way with same
NULL value. The only thing I found was the Covariates function in the popPK
package, which makes use of Xpose, developed by Christoffer Tornoe while he was
at FDA. http://www2.uaem.mx/r-mirror/web/packages/popPK/popPK.pdf
But this package looks like to be no longer supported and has been removed from
the CRAN.
Has anyone developed such a package?
With best regards / Mit freundlichen Grüßen / Cordialement / 祝好 / よろしくお願いします
Pascal
Pascal Girard
Director, Pharmacometry
Merck Serono | Global Early Development
"Merck – Living Innovation"
Merck Institute for Pharmacometrics - Merck Serono S.A.
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