Displaying 20 results from an estimated 200 matches similar to: "Unlist alternatives?"
2006 Mar 21
1
Scaling behavior ov bVar from lmer models
Hi all,
To follow up on an older thread, it was suggested that the following
would produce confidence intervals for the estimated BLUPs from a linear
mixed effect model:
OrthoFem<-Orthodont[Orthodont$Sex=="Female",]
fm1OrthF. <- lmer(distance~age+(age|Subject), data=OrthoFem)
fm1.s <- coef(fm1OrthF.)$Subject
fm1.s.var <- fm1OrthF. at bVar$Subject
fm1.s0.s <-
2013 Feb 05
1
lmer - BLUP prediction intervals
Dear all
I have a model that looks like this:
m1 <- lmer(Difference ~ 1+ (1|Examiner) + (1|Item), data=englisho.data)
I know it is not possible to estimate random effects but one can
obtain BLUPs of the conditional modes with
re1 <- ranef(m1, postVar=T)
And then dotplot(re1) for the examiner and item levels gives me a nice
prediction interval. But I would like to have the prediction
2006 Sep 23
1
variance-covariance structure of random effects in lme
Dear R users,
I have a question about the patterned variance-covariance structure for the random effects in linear mixed effect model.
I am reading section 4.2.2 of "Mixed-Effects Models in S and S-Plus" by Jose Pinheiro and Douglas Bates.
There is an example of defining a compound symmetry variance-covariance structure for the random effects in a
split-plot experiment on varieties of
2006 Apr 13
3
Penalized Splines as BLUPs using lmer?
Dear R-list,
I?m trying to use the lmer of the lme4 package to fit a linear mixed model
of the form
Y = Xb + Zu + e
and I can?t figure out how to control the covariance structure of u. I want
u ~ N(0,sigma^2*I).
More precisely I?m trying to smooth a curve through data using the
"Penalized Splines as BLUPs" method as described in Ruppert, Wand &
Carroll (2003).
So I have Z = [Z1
2011 Jul 08
3
Efectos aleatorios, interaccions y SNK, LSD o Tukey
Queridos R-users:
Tengo una duda que hace mucho tiempo que estoy intentando resolver, os
explico a modo de ejemplo:
Tengo estos efectos: Año(5 niveles),Localidad (10 niveles) y genotipo
(3 niveles), año y localidad son aleatorios y genotipo es fijo (los he
escogido yo).
Me gustaría hacer obtener una tabla parecida a la Tabla Anova donde
aparezca cada factor y sus interacciones y
2004 Apr 08
0
lme, mixed models, and nuisance parameters
I have the following dataset:
96 plots
12 varieties
2 time points
The experiment is arranged as follows:
A single plot has two varieties tested on it.
With respect to time points, plots come in 3 kinds:
(1) varietyA, timepoint#1 vs. variety B, timepoint#1
(2) varietyA timepoint #2 vs. varietyB timepoint #2
(3) varietyA timepoint #1 vs. variety A timepoint#2
- there are 36 of each kind
2002 Aug 16
2
[nlme] BLUPs for a new subject in a fitted lme model?
I am seeking for a method to calculate, given a fitted lme model
and some data for a subject, the random effects predictors
for this subject. I can only find predictors for the subjects used in
creating the fit. Of course I could just add the subject and redo the fit.
But I want to avoid just this refitting.
Thanks for help
wbk
2006 Oct 05
1
mixed models: correlation between fixed and random effects??
Hello,
I built 4 mixed models using different data sets and standardized variables
as predictors.
In all the models each of the fixed effects has an associated random effect
(same predictor).
What I find is that fixed effects with larger (absolute) standardized
parameter estimates have also a higher estimate of the related random
effect. In other words, the higher the average of the absolute
2007 Mar 23
1
lmer estimated scale
I have data consisting of binary responses from a large number of
subjects on seven similar items. I have been using lmer with
(crossed) random effects for subject and item. These effects are
almost always (in the case of subject, always) significant additions
to the model, testing this with anova. Including them also increases
the Somers' Dxy value substantially.
Even without those
2010 Oct 04
1
Ridge regression and mixed models
Dear R users,
An equivalence between linear mixed model formulation and penalized regression
models (including the ridge regression and penalized regression splines) has
proven to be very useful in many aspects. Examples include the use of the lme()
function in the library(nlme) to fit smooth models including the estimation of a
smoothing parameter using REML. My question concerns the use of
2011 Apr 16
3
lme4 problem: model defining and effect estimation ------ question from new bird to R community from SAS community
Hi R community,
I am new bird to R and moved recently from SAS. I am no means expert on
either but very curious learner. So your help crucial for me to learn R.
I have already got positive expression.
I was trying to fit a mixed model in animal experiment but stuck at simple
point. The following similar example is from SAS mixed model pp 212.
# data
genetic_evaluation <-
2014 Apr 21
7
Bug#745419: xen-utils-4.1: Pygrub fails to boot from LVM LV when something installed in the volume boot record
Package: xen-utils-4.1
Version: 4.1.4-3+deb7u1
Severity: important
When an LVM LV that serves as the root disk for a Xen DomU contains a boot
loader (or possibly other data) in its volume boot record, pygrub fails to boot
it, printing "Error: boot loader didn't return any data" before exiting.
I think this is because of the function "is_disk_image" on line 45 of
2009 Mar 18
2
multiple barplot
Dear all,
I want to put 9 barplots side by side. My code below only print 5 names from
9 names I gave.
Problem: how to print all of those 9 names? I use cex=0.8 but did not work,
it gave me error message.
d<-matrix(rpois(45,3),5,9)
barplot(d,beside=T,col=rainbow(5),names=c("CRTL","LSB","ONEMKR",
2009 Sep 23
1
BLUP with missing data
hello guys, I need to do a BLUP in the simplest model
y = Xm + Zg + e
however I have missing data in the analysis which I can?t consider as
0(zero). So I need to generate the matrix X'Z, Z'X and Z'Z step by step; I
can?t use
crossprod(x) #neither
X'X <- t(x)%*%x
because I should skip the elements with missing data in the matrix
I?ll try to be more clear,
supposing
a matrix x
2006 Aug 16
1
[SPAM] - RE: REML with random slopes and random intercepts giving strange results - Bayesian Filter detected spam
Can you provide the summary(m2) results?
> -----Original Message-----
> From: Simon Pickett [mailto:S.Pickett at exeter.ac.uk]
> Sent: Wednesday, August 16, 2006 7:14 AM
> To: Doran, Harold
> Cc: r-help at stat.math.ethz.ch
> Subject: [SPAM] - RE: [R] REML with random slopes and random
> intercepts giving strange results - Bayesian Filter detected spam
>
> Hi again,
2014 Apr 22
0
Bug#745419: Bug#745419: xen-utils-4.1: Pygrub fails to boot from LVM LV when something installed in the volume boot record
On Mon, 2014-04-21 at 15:43 +0200, Sjors Gielen wrote:
> Package: xen-utils-4.1
> Version: 4.1.4-3+deb7u1
> Severity: important
>
> When an LVM LV that serves as the root disk for a Xen DomU contains a boot
> loader (or possibly other data) in its volume boot record, pygrub fails to boot
> it, printing "Error: boot loader didn't return any data" before exiting.
2006 Jul 31
0
Three questions about a model for possibly periodic data with varying amplitude
Hi dear R community,
I have up to 12 measures of a protein for each of 6 patients, taken
every two or three days. The pattern of the protein looks periodic,
but the height of the peaks is highly variable. It's something like
this:
patient <- data.frame(
day = c(1, 3, 5, 8, 10, 12, 15, 17, 19, 22, 24, 26),
protein = c(5, 3, 10, 7, 2, 8, 25, 12, 7, 20, 10, 5)
)
plot(patient$day,
2007 Sep 26
1
Accessing the fixed- and random-effects variance-covariance matrices of an nlme model
I would appreciate confirmation that the function vcov(model.nlme)
gives the var-cov matrix of the fixed effects in an nlme model.
Presumably the random-effects var-cov matrix is given by cov(ranef
(model.nlme)?
Rob Forsyth
2009 Feb 19
1
Roadmap for selecting an approach to analyzing repeated measures data
Dear Group,
At http://biostat.mc.vanderbilt.edu/tmp/summary.pdf I have put a draft
of a roadmap for choosing a method for analyzing serial (longitudinal)
data. If anyone has feedback about this, including adding criteria for
judging methods that I may have missed, I would appreciate hearing from you.
Thanks
Frank
--
Frank E Harrell Jr Professor and Chair School of Medicine
2012 Dec 11
1
Interpretation of ranef output
Hello.
I'm running a generalized linear model and am interested in using the
random effects that are output for further analysis. My random effect is
interacting with two different fixed effects (which which are factors with
two levels each). When I retrieve the random effects I get something like
this:
(Intercept) nutrient (Intercept) light (Intercept)
Aa-0 0.59679192