similar to: Question about linear mixed effects model (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

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",

Hello Arno, Can apply the patch directly or should I recompile nut? Best regards, Panagiotis On 3/4/2015 5:06 ??, Arnaud Quette wrote: > Hello Panagiotis > > 2015-04-03 14:28 GMT+02:00 Panagiotis Kritikakos > <panagiotis.kritikakos at nikitec.gr > <mailto:panagiotis.kritikakos at nikitec.gr>>: > > Hello Arno, > > Question: have you also

Hello Arno, FreeNAS doesn't come with a compiler and I had to compile with the patch on FreebBSD-9.3 and then copy the produced mge-shut. Unfortunately it didn't work out. For every try I was getting "Connection Refused" and when I tried /usr/local/libexec/nut/mge-shut -D -a <ups_name> I was always getting 'No matching HID UPS found'. I returned back to the

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

Hello Arno, Thanks for the quick reply. FreeNAS is FreeBSD-based. Yes, I could test a patch. As I have mentioned, this behavior is not seen at every single reboot but after most reboots. Also, some times, the connectivity can be lost without even rebooting. That is not very often can have happened a few times. Best regards, Panagiotis On 2/4/2015 5:44 ??, Arnaud Quette wrote: > Hello

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

Hello, I'm trying to install FreeBSD 9.1 amd64 on an IBM x3550 M3 server. Installation went smoothly, RAID controller and network cards were successfully recognised. But, after the installation, the server fails to boot from disk. There were some posts, about two years ago, in this list implying that the problem lies in UEFI but I couldn't find any clear solution. Any suggestions would

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 being

Is it just me, or freebsd-update isn't yet shipping the openssl updates? I'm trying (on an SMP machine) to fetch them, but there seem to be none available. I'd like to confirm that sleep deprivation isn't the culprit here, so I've checked in /usr/local/freebsd-update/work/ and the subdirectory with the highest number contains the SA-06:21 files. Anyone seen that clue bat

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 ~

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

Hello Arno, > Question: have you also tested oldmge-shut? > Otherwise, that might be interesting to do so and send back the > results of these tests... Yes, I've tried this as well with worse results unfortunately. This driver seems to be even more unstable. When it gets able to set communication with the UPS (which is not always the case), it usually lost it again after a while.

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)

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

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;

Hello, Last year, I installed CentOS 5.2 on an HP Proliant Server. Along with other packages, the gmp and gmp-devel version 4.1.4 packages were installed. To the best of my knowledge these packages do not come from the gmp team. Recently, I built an rpm package for gmp 5.0.1 for CentOS 5.2. I tried to update the gmp package by command rpm -Uvh gmp-5.0.1-1.x86_64.rpm but the update failed

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

the content of th character vector (of length 1) is as follows: a <- "something2 ....pat1 name1 pat2 something2....pat1 name2 pat2....pat1 name3 pat2 " I would like to extract the character bewteen pat1 and pat2. That's to say, I would like to get a vecter of c("name1", "name2","name3"). What I did is use strsplit() twise. But I wonder if there

Dear R-users! I am using R 1.7.0, under Windows XP. Having some hospital discharge data (admission date and discharge date for each patient), I want to get the number of patients in the hospital on a given date. My data look like (simple example): > x <- data.frame(patid=c("pat1", "pat2"), adm.date = c("15.03.2002", "16.03.2002"),