Displaying 20 results from an estimated 300 matches similar to: "F distribution from lme()?"
2007 Oct 31
0
Problems with generating F-distr from lme()
Dear all,
Using the data set and code below, I am interested in modelling how egg
temperature (egg.temp)
is related to energy expenditure (kjday) and clutch size (treat) in
incubating birds using the
lme-function. I wish to generate the F-distribution for my model, and have
tried to do so using
the anova()-function. However, in the resulting anova-table, the parameter
kjday has gone from
2007 Oct 16
0
Help with repeated measures!
Hello all,
I'm an R novice, recently trying to implement R in my research. Using the
data frame below, I want to construct a repeated measures model, with energy
expenditure (kjday) as dependent of treatment (code)
using mass as a covariate.
ind mass kjday code
79 15.8 45.216 3
42 16.5 44.64 3
10 14.85 45.216 3
206 15.75 45.216 3
23 12.15 42.336 3
5 14.6 51.264 3
....
79 16.9
2012 Nov 24
3
Help!!!!!
Dear R users.
I am little lost and i need your help.
I have such data.
DATE i Symptomes t
1 2009-04-24 Mexique 0 14358
2 2009-04-24 usa 0 14358
3 2009-04-26 Mexique 18 14360
4 2009-04-26 usa 100 14360
5 2009-04-27 Canada 6 14361
6 2009-04-27
2010 Sep 16
1
Help for an absolutely r-noob
Hello together,
I am an absolute noob in R and therefore I need help urgently. I have
received a script from my tutor with plot functions in it. However, I can'
manage to adapt these plots.
The hole script is as follows:
setwd("E:/")
##### (1) Read data ###
dat <- read.table("Komfort_Tatsaechliche_ID_Versuchsreihe_1.txt",
header=TRUE,
sep="\t",
2003 Jun 17
1
lme() vs aov(y ~ A*B + Error(aa %in% A + bb %in% B)) [repost]
I've posted the following to R-help on May 15.
It has reproducible R code for real data -- and a real
(academic, i.e unpaid) consultion background.
I'd be glad for some insight here, mainly not for myself.
In the mean time, we've learned that it is to be expected for
anova(*, "marginal") to be contrast dependent, but still are
glad for advice if you have experience.
Thank
2001 Dec 23
1
aov for mixed model (fixed and random)?
I'm starting to understand fixed and random effects, but I'm
puzzled a bit. Here is an example from Hays's textbook (which is
great at explaining fixed vs. random effects, at least to dummies
like me), from the section on mixed models. You need
library(nlme) in order to run it.
------
task <- gl(3,2,36) # Three tasks, a fixed effect.
subj <- gl(6,6,36) # Six subjects, a random
2012 Dec 04
6
Help for a function
Hello all,
I need a help.
I am modeling a disease and a create a R function like that:
Lambda<-function (x,date1,r,h,a){
ndate1 <- as.Date(date1, "%d/%m/%Y")
t1 <- as.numeric(ndate1)
x[order(x$i),]
t <-x[,"t"]
i <-x[,"i"]
CONTAGIEUX <-x[,"CONTAGIEUX"]
while ( t1 < min(t) ){
for (i in 1:length(i) ){
{for (j in
2005 Jul 18
1
Nested ANOVA with a random nested factor (how to use the lme function?)
Hi,
I am having trouble using the lme function to perform a nested ANOVA
with a random nested factor.
My design is as follows:
Location (n=6) (Random)
Site nested within each Location (n=12) (2 Sites nested within each
Location) (Random)
Dependent variable: sp (species abundance)
By using the aov function I can generate a nested ANOVA, however this
assumes that my nested
2007 Jun 28
2
aov and lme differ with interaction in oats example of MASS?
Dear R-Community!
The example "oats" in MASS (2nd edition, 10.3, p.309) is calculated for aov and lme without interaction term and the results are the same.
But I have problems to reproduce the example aov with interaction in MASS (10.2, p.301) with lme. Here the script:
library(MASS)
library(nlme)
options(contrasts = c("contr.treatment", "contr.poly"))
# aov: Y ~
2004 Jun 11
2
lme newbie question
Hi
I try to implement a simple 2-factorial repeated-measure anova in the
lme framework and would be grateful for a short feedback
-my dependent var is a reaction-time (rt),
-as dependent var I have
-the age-group (0/1) the subject belongs to (so this is a
between-subject factor), and
-two WITHIN experimental conditions, one (angle) having 5, the other
3 (hands) factor-levels;
2009 Apr 01
3
How to prevent inclusion of intercept in lme with interaction
Dear friends of lme,
After so many year with lme, I feel ashamed that I cannot get this to work.
Maybe it's a syntax problem, but possibly a lack of understanding.
We have growth curves of new dental bone that can well be modeled by a
linear growth curve, for two different treatments and several subjects as
random parameter. By definition, newbone is zero at t=0, so I tried to force
the
2008 Oct 15
2
Network meta-analysis, varConstPower in nlme
Dear Thomas Lumley, and R-help list members,
I have read your article "Network meta-analysis for indirect treatment
comparisons" (Statist Med, 2002) with great interest. I found it very
helpful that you included the R code to replicate your analysis;
however, I have had a problem replicating your example and wondered if
you are able to give me a hint. When I use the code from the
2004 Jul 16
1
Fixed and random factors in aov()
Hi,
I'm confused about how to specify random and fixed factors in an aov()
term. I tried to reproduce a textbook example: One fixed factor (Game, 4
levels) and one random factor (Store, 12 levels), response is Points.
The random factor Store is nested in Game. I tried
> str(kh.df)
`data.frame': 48 obs. of 4 variables:
$ Subj : Factor w/ 48 levels
2003 Apr 08
2
Basic LME
Hello R Users,
I am investigating the basic use of the LME function, using the following example;
Response is Weight, covariate is Age, random factor is Genotype
model.lme <- lme (Weight~Age, random=~ 1|Genotype)
After summary(model.lme), I find that the estimate of Age is 0.098 with p=0.758.
I am comparing the above model with the AOV function;
model.aov <- aov (Weight~Age + Genotype)
2005 Sep 19
1
How to mimic pdMat of lme under lmer?
Dear members,
I would like to switch from nlme to lme4 and try to translate some of my
models that worked fine with lme.
I have problems with the pdMat classes.
Below a toy dataset with a fixed effect F and a random effect R. I gave
also 2 similar lme models.
The one containing pdLogChol (lme1) is easy to translate (as it is an
explicit notation of the default model)
The more parsimonious
2007 May 24
4
Function to Sort and test AIC for mixed model lme?
Hi List
I'm running a series of mixed models using lme, and I wonder if there
is a way to sort them by AIC prior to testing using anova
(lme1,lme2,lme3,....lme7) other than by hand.
My current output looks like this.
anova
(lme.T97NULL.ml,lme.T97FULL.ml,lme.T97NOINT.ml,lme.T972way.ml,lme.T97fc.
ml, lme.T97ns.ml, lme.T97min.ml)
Model df AIC BIC logLik
2006 Jan 31
1
lme in R (WinXP) vs. Splus (HP UNIX)
R2.2 for WinXP, Splus 6.2.1 for HP 9000 Series, HP-UX 11.0.
I am trying to get a handle on why the same lme( ) code gives
such different answers. My output makes me wonder if the
fact that the UNIX box is 64 bits is the reason. The estimated
random effects are identical, but the fixed effects are very
different. Here is my R code and output, with some columns
and rows deleted for space
2011 Oct 04
1
Question about linear mixed effects model (nlme)
Hi,
I applied a linear mixed effect model in my data using the nlme package.
lme2<-lme(distance~temperature*condition, random=~+1|trial, data) and then
anova.
I want to ask if it is posible to get the least squares means for the
interaction effect and the corresponding 95%ci. And then plot this values.
Thank you
Panagiotis
--
View this message in context:
2012 Sep 14
1
linear mixed-effects models with two random variables?
Dear R users,
Does anyone knows how to run a glmm with one fixed factor and 2 random
numeric variables (indices)? Is there any way to force in the model a
separate interaction of those random variables with the fixed one?
I hope you can help me.
#eg.
Reserve <- rep(c("In","Out"), 100)
fReserve <- factor(Reserve)
DivBoulders <- rep
2006 Oct 05
4
glm with nesting
I just had a manuscript returned with the biggest problem being the
analysis. Instead of using principal components in a regression I've
been asked to analyze a few variables separately. So that's what I'm
doing.
I pulled a feather from young birds and we quantified certain aspects of
the color of those feathers. Since I often have more than one sample
from a nest, I thought I