Displaying 16 results from an estimated 16 matches for "nonrandomized".
2004 Sep 14
1
R-2.0.0 CMD check . and datasets
Hello everyone
I'm having a little difficulty with R-2.0.0 CMD check. My field is
Bayesian calibration of computer models.
The problem is that I have a large collection of toy datasets, that
in R-1.9.1 were specified with lines
like this:
x.toy <- 1:6
y.toy <- computer.model(x.toy)
z.toy <- reality(x.toy)
in file ./data/toys.R ; functions computer.model() and reality() are
2004 Sep 14
1
R-2.0.0 CMD check . and datasets
Hello everyone
I'm having a little difficulty with R-2.0.0 CMD check. My field is
Bayesian calibration of computer models.
The problem is that I have a large collection of toy datasets, that
in R-1.9.1 were specified with lines
like this:
x.toy <- 1:6
y.toy <- computer.model(x.toy)
z.toy <- reality(x.toy)
in file ./data/toys.R ; functions computer.model() and reality() are
2009 Jun 19
0
package JM -- version 0.3-0
Dear R-users,
I'd like to announce the release of the new version of package JM (soon
available from CRAN) for the joint modelling of longitudinal and
time-to-event data using shared parameter models. These models are
applicable in mainly two settings. First, when focus is in the
time-to-event outcome and we wish to account for the effect of a
time-dependent covariate measured with
2010 Mar 18
0
package JM -- version 0.6-0
Dear R-users,
I'd like to announce the release of the new version of package JM (soon
available from CRAN) for the joint modelling of longitudinal and
time-to-event data using shared parameter models. These models are
applicable in mainly two settings. First, when focus is in the
time-to-event outcome and we wish to account for the effect of a
time-dependent covariate measured with
2010 Dec 15
0
package JM -- version 0.8-0
Dear R-users,
I'd like to announce the release of the new version of package JM (soon
available from CRAN) for the joint modeling of longitudinal and
time-to-event data using shared parameter models. These models are
applicable in mainly two settings. First, when focus is in the survival
outcome and we wish to account for the effect of a time-dependent
covariate measured with error.
2004 Aug 16
0
Interacting with Clusters...
...g on developing this sort of point-and-click
capability in R? I would be very interested in becoming an alpha or beta
tester of this functionality.
If some computer scientist is looking for a thesis topic involving
applications of graphics and statistical methods in health care
(randomized or nonrandomized studies), I would be happy to send a recent
white paper on the methodology I visualize. On top of my work at Lilly, I
am an adjunct professor of biostatistics at Indiana University Medical
School and would be willing to participate on a thesis committee.
For example, I can perform almost all o...
2009 Jun 19
0
package JM -- version 0.3-0
Dear R-users,
I'd like to announce the release of the new version of package JM (soon
available from CRAN) for the joint modelling of longitudinal and
time-to-event data using shared parameter models. These models are
applicable in mainly two settings. First, when focus is in the
time-to-event outcome and we wish to account for the effect of a
time-dependent covariate measured with
2009 Dec 16
0
Duration model with sample selection (or selectivity)
Hello All,
I am interested in estimating a duration model (also known as survival
analysis or event-history analysis). I use an economic dataset. In
economics terms, the model is "duration model with sample selection (or
selectivity)." The time spell variable is only observed for a sample
that meets certain requirements so the sample is nonrandom. Does anybody
know any R package that
2010 Mar 18
0
package JM -- version 0.6-0
Dear R-users,
I'd like to announce the release of the new version of package JM (soon
available from CRAN) for the joint modelling of longitudinal and
time-to-event data using shared parameter models. These models are
applicable in mainly two settings. First, when focus is in the
time-to-event outcome and we wish to account for the effect of a
time-dependent covariate measured with
2010 Dec 15
0
package JM -- version 0.8-0
Dear R-users,
I'd like to announce the release of the new version of package JM (soon
available from CRAN) for the joint modeling of longitudinal and
time-to-event data using shared parameter models. These models are
applicable in mainly two settings. First, when focus is in the survival
outcome and we wish to account for the effect of a time-dependent
covariate measured with error.
2011 Sep 28
0
package JM -- version 0.9-0
Dear R-users,
I'd like to announce the release of the new version of package JM (soon
available from CRAN) for the joint modeling of longitudinal and
time-to-event data using shared parameter models. These models are
applicable in mainly two settings. First, when focus is in the survival
outcome and we wish to account for the effect of an endogenous (aka
internal) time-dependent
2011 Sep 28
0
package JM -- version 0.9-0
Dear R-users,
I'd like to announce the release of the new version of package JM (soon
available from CRAN) for the joint modeling of longitudinal and
time-to-event data using shared parameter models. These models are
applicable in mainly two settings. First, when focus is in the survival
outcome and we wish to account for the effect of an endogenous (aka
internal) time-dependent
2012 Jul 10
0
package JM -- version 1.0-0
Dear R-users,
I'd like to announce the release of version 1.0-0 of package JM (already
available from CRAN) for the joint modeling of longitudinal and
time-to-event data using shared parameter models. These models are
applicable in mainly two settings. First, when focus is in the survival
outcome and we wish to account for the effect of an endogenous (aka
internal) time-dependent
2012 Jul 10
0
package JM -- version 1.0-0
Dear R-users,
I'd like to announce the release of version 1.0-0 of package JM (already
available from CRAN) for the joint modeling of longitudinal and
time-to-event data using shared parameter models. These models are
applicable in mainly two settings. First, when focus is in the survival
outcome and we wish to account for the effect of an endogenous (aka
internal) time-dependent
2007 Feb 10
1
SAS, SPSS Product Comparison Table
Hi All,
My paper "R for SAS and SPSS Users" received a bit more of a reaction
than I expected. I posted the link
(http://oit.utk.edu/scc/RforSAS&SPSSusers.pdf) about 12 days ago on
R-help and the equivalent SAS and SPSS lists. Since then people have
downloaded it 5,503 times and I've gotten lots of questions along the
lines of, "Surely R can't do for free what [fill in
2008 Jul 08
8
Sum(Random Numbers)=100
Hi R,
I need to generate 50 random numbers (preferably poisson), such that
their sum is equal to 100. How do I do this?
Thank you,
Shubha
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