Displaying 20 results from an estimated 20000 matches similar to: "Problem with nlme package"
2005 Jan 28
3
Conflicts using Rcmdr, nlme and lme4
Hello all!
R2.0.1, W2k. All packages updated.
I?m heavily dependant on using mixed models. Up til?now I have used
lme() from nlme as I have been told to. Together with estimable() from
gmodels it works smooth. I also often run Rcmdr, mostly for quick
graphics.
After using Rcmdr, on reopening the R workspace all help libraries for
Rcmdr (22 !) loads, among them nlme, but not Rcmdr itself. Why?
2005 Jan 03
1
different DF in package nlme and lme4
Hi all
I tried to reproduce an example with lme and used the Orthodont
dataset.
library(nlme)
fm2a.1 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1 | Subject)
anova(fm2a.1)
> numDF denDF F-value p-value
> (Intercept) 1 80 4123.156 <.0001
> age 1 80 114.838 <.0001
> Sex 1 25 9.292 0.0054
or alternatively
2012 Jun 06
3
Sobel's test for mediation and lme4/nlme
Hello,
Any advice or pointers for implementing Sobel's test for mediation in
2-level model setting? For fitting the hierarchical models, I am using
"lme4" but could also revert to "nlme" since it is a relatively simple
varying intercept model and they yield identical estimates. I apologize for
this is an R question with an embedded statistical question.
I noticed that a
2004 Aug 27
2
degrees of freedom (lme4 and nlme)
Hi, I'm having some problems regarding the packages
lme4 and nlme, more specifically in the denominator
degrees of freedom. I used data Orthodont for the two
packages. The commands used are below.
require(nlme)
data(Orthodont)
fm1<-lme(distance~age+ Sex,
data=Orthodont,random=~1|Subject, method="REML")
anova(fm1)
numDF DenDF F-value p-value
(Intercept) 1
2004 Oct 08
1
Bug in nlme under version 2.0.0
Dear all,
Under version 2.0.0, I get the error below when calling summary() on a lme-object, whereas it works under version 1.9.1 (well, it did last week, before I upgraded). Any help on this?
Thx in advance
S??ren
> library(nlme)
> mf <- formula(Weight~Cu*(Time+I(Time^2)+I(Time^3)))
> lme1 <- lme(mf, data = dietox, random=~1|Pig)
> summary(lme1)
Linear mixed-effects model fit
2010 Oct 25
3
question in using nlme and lme4 for unbalanced data
Hello:
I have an two factorial random block design. It's a ecology
experiment. My two factors are, guild removal and enfa removal. Both
are two levels, 0 (no removal), 1 (removal). I have 5 blocks. But
within each block, it's unbalanced at plot level because I have 5
plots instead of 4 in each block. Within each block, I have 1 plot
with only guild removal, 1 plot with only enfa removal,
2011 Sep 12
1
Multilevel model in lme4 and nlme
Dear list,
I am trying to fit some mixed models using packages lme4 and nlme.
I did the model selection using lmer but I suspect that I may have some
autocorrelation going on in my data so I would like to have a look using the
handy correlation structures available in nlme.
The problem is that I cannot translate my lmer model to lme:
mod1<- lmer(y~x + (1|a:b) + (1|b:c), data=mydata)
2005 May 17
1
setting value arg of pdSymm() in nlme
Dear All,
I wish to model random effects that have known between-group covariance
structure using the lme() function from library nlme. However, I have yet
to get even a simple example to work. No doubt this is because I am
confusing my syntax, but I would appreciate any guidance as to how. I have
studied Pinheiro & Bates carefully (though it's always possible I've
missed
2007 May 03
2
nlme fixed effects specification
dear R experts:
sorry, I have to ask this again. I know that the answer is in section
7.2 of "S Programming," but I don't have the book (and I plan to buy
the next edition---which I hope will be titled S/R programming ;-) ).
I believe the following yields a standard fixed-effects estimation:
fixed.effects = as.factor( as.integer( runif(100)*10 ) )
y=rnorm(100); x=rnorm(100);
2007 Jun 20
2
Linear Mixed Models with nlme, more than one random effect
Hi, I' trying to learn how to use lme for Linear Mixed Models and I have a
problem when I have to include more than one random effect in my model. I
know that this could be a stupid question to ask, but I'm not able to solve
it by myself... One example: if my model is
response = operator + block + day
with operator and block as fixed effects and day as random effect, I use
res.lme
2006 Apr 08
1
dim(x) error message in lme (nlme package)
Hello
I am trying to analyse mortality data from fish larvae using lme from
the package nlme as well as using lmer in the package lme4
Response is DeathDay
Fixed factor is Treatment
Random factors are Clucth, Cup
Design: Cup nested in Clutch
If I do this in lme, I use the syntax:
model1 <- lme(DeathDay ~ Treatment, random=~ 1 | Clutch/Cup)
summary(model1)
I get the first part of the output,
2024 Jan 08
1
how to specify uncorrelated random effects in nlme::lme()
Dear professor,
I'm using package nlme, but I can't find a way to specify two uncorrelated random effects. For example, a random intercept and a random slope. In package lme4, we can specify x + (x ll g) to realize, but how in nlme?
Thanks!
????????????????????????
Zhen Wang
Graduate student, Department of Medical Statistics, School of Public Health, Sun Yat-sen
2005 Jun 09
2
can nlme do the complex multilevel model?
data from multilevel units,first sample the class ,and then the student in calss.following is the 2-level model. and the level-1 model deals with the student,and the level-2 model deals with the class level the students belong to.
Level-1 Model
Y = B0 + B1*(ZLEAD) + B2*(ZBUL) + B3*(ZSHY) + R
Level-2 Model
B0 = G00 + U0
B1 = G10 + G11*(ZWARMT) + U1
B2 = G20 + G21*(ZWARMT) + G22*(ZABLET) +
2005 Dec 12
2
convergence error (lme) which depends on the version of nlme (?)
Dear list members,
the following hlm was constructed:
hlm <- groupedData(laut ~ design | grpzugeh, data = imp.not.I)
the grouped data object is located at and can be downloaded:
www.anicca-vijja.de/lg/hlm_example.Rdata
The following works:
library(nlme)
summary( fitlme <- lme(hlm) )
with output:
...
AIC BIC logLik
425.3768 465.6087 -197.6884
Random effects:
2007 Nov 12
1
Using lme (nlme) to find the conditional variance of the random effects
Using lmer in the lme4 package, you can compute the conditional
variance-covariance matrix of the random effects using the bVar slot:
bVar: A list of the diagonal inner blocks (upper triangles only) of the
positive-definite matrices on the diagonal of the inverse of ZtZ+Omega.
With the appropriate scale factor (and conversion to a symmetric matrix)
these are the conditional variance-covariance
2013 Mar 04
1
Choosing nlme or lme4?
Hi List,
I’ m analysing the selectivity of
resting site use by forest carnivores through mixed modelling techniques and I
wonder which will be the best r package to deal with several aspects simultaneously:
- binomial
variable response;
- possible
spatial and/or temporal correlation;
I have tried nlme (lme function) and
lme4 (lmer function) packages, however I realize that the
2006 Aug 22
1
Marginal Predicitions from nlme and lme4
Is there a way (simple or not) to get the marginal prediction from lme
(in nlme) and/or lmer (in lme4)?
Rick B.
2010 Mar 18
2
Please Post Planned Contrasts Example in lme {nlme}
Hi I am running some linear and non-linear mixed effect models and would like to do some planned contrasts (a priori contrasts)
I have looked in the help and in many forums and it seems possible to do so but don't understand how to write the function and I couldn't find an example in Pinheiro and Bates.
lme {nlme} has a contrasts argument but I can't understand how to code it.
2005 Apr 05
1
nlme & SASmixed in 2.0.1
I assigned a class the first problem in Pinheiro & Bates, which uses the
data set PBIB from the SASmixed package. I have recently downloaded
2.0.1 and its associated packages. On trying
library(SASmixed)
data(PBIB)
library(nlme)
plot(PBIB)
I get a warning message
Warning message:
replacing previous import: coef in: namespaceImportFrom(self,
asNamespace(ns))
after library(nlme) and a
2006 Aug 03
2
fitting a model with the nlme package
Dear all,
I am analyzing some data that requires a mixed model. I have been
reading Pinheiro and Bates' book,
but cannot find the notation to fit the following model:
Suppose I have the dataset below. Here I am fitting variable p as a
fixed effect, variable h
as a random effect and variable t as nested within h. I would like to
include the variable j as well
as an independent (non-nested)