similar to: Basic LME

Hello All, Is there a way of producing an ANOVA table split into contrasts, thus showing the contrasts sums of squares and associated p-values? Thanks, Martin. Martin Hoyle, School of Life and Environmental Sciences, University of Nottingham, University Park, Nottingham, NG7 2RD, UK Webpage: http://myprofile.cos.com/martinhoyle

Dear R Users, I suppose this is a school boy question, but here it is anyway. I'm trying to re-create the residuals for a poisson GLM with simulated data; x<-rpois(1000,5) model<-glm(x~1,poisson) my.resids<-(log(x)- summary(model)$coefficients[1]) plot(my.resids,residuals(model)) This shows that my calculated residuals (my.resids) are not the same as residuals(model). p 65 of

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",

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

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

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

Dear Greg, Thanks for the new release. The decomposition of the SSQ is just what I need! Regards, Martin. Martin Hoyle, School of Life and Environmental Sciences, University of Nottingham, University Park, Nottingham, NG7 2RD, UK Webpage: http://myprofile.cos.com/martinhoyle >>> gregory_r_warnes at groton.pfizer.com 10/30/02 07:16PM >>> Version 0.7.3 of the gregmisc package

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

Hi, Can someone tell me how to normalize a data set so that the mean of the set is 0 and the variance is 1. As I understand, when you calculate the principle components of a data set through correlation as < princomp( dataset, cor=T ) > then a similar calculation is performed. I would like to know how I can perform such a calulation directly. Any help would be greatly appreciated. Many

Hello all. I have a simple barplot with sixteen different segments. When I plot my data, only five or six of the labels are showing in the x-axis. How do go get them all to show? Can I set them at a 45.degree angle? Thank you. Jess -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

Hi, I'm trying to use the command "glm.nb" in library(MASS) to test for a significant difference in the aggregation parameter "theta" between the three levels of a factor. Any help gratefully received! Martin. Martin Hoyle, School of Life and Environmental Sciences, University of Nottingham, University Park, Nottingham, NG7 2RD, UK Webpage:

Dear R-help members, I'm trying to run LME model on some behavioral data and need confirmations about what I'm doing... Here's the story... I have some behavioral reaction time (RT) data (participants have to detect dome kind of auditory stimuli). the dependant variable is RT measured in milliseconds. 61 participants were tested separated in 4 age groups (unblanced groups,

I am new to R. I am going to by one of the following book: 1. William N. Venables and Brian D. Ripley. Modern Applied Statistics with S-Plus. Third Edition. Springer, 1999. ISBN 0-387-98825-4. 2. The Fourth Edition of the book from point 1. 3. `S Programming' by W. N. Venables and B. D. Ripley Springer. ISBN 0-387-98966-8, 2000. I can only by one of the above books. Q1. I have found

Dear All, I'm rather a beginner on nested ANOVAs, so here goes with my 2 questions; Qu 1: I'm modelling the number of galls on a leaf (the response variable) as a function of; the tree on which I find the leaf, the branch on which I find the leaf. Then, the tree and the branch are both random factors, and I'm quite happy that I should write; aov(galls~tree/branch +

#Hello, #I have a question about obtaining results from a loop I have written. #Below is a sample of individual genotypes from a genetic question I am working on called "P.genotype.sample ". P.genotype.sample<-matrix(10,10,10) P.genotype.sample[,1]<-c(2,2,1,5,1,1,5,6,1,3) P.genotype.sample[,2]<-c(6,3,3,6,8,1,6,7,2,3) P.genotype.sample[,3]<-c(2,2,2,3,3,2,2,2,3,3)

#Hello, #I have would like to paste a single column of a matrix # in pair wise fashion with other columns based upon # even and odd column numbers. # I can do it in a very clunky fashion and I know there # must be a better way. below is a sample matrix and my extremely # clunky code that gets the job done for a small matrix, but i plan to # do this on a much grander scale. any help would be very

Hi. I was wondering if anyone might have some suggestions about how I can overcome a problem of "iteration limit reached without convergence" when fitting a mixed effects model. In this study: Outcome is a measure of heart action Age is continuous (in weeks) Gender is Male or Female (0 or 1) Genotype is Wild type or knockout (0 or 1) Animal is the Animal ID as a factor

Hi, I am conducting an association analysis of genotype and a phenotype such as cholesterol level as an outcome and the genotype as a regressor using multiple linear regression. There are 3 possibilities for the genotype AA, AG, GG. There are 5 people with the AA genotype, 100 with the AG genotype and 900 with the GG genotype. I coded GG genotype as 1, AG as 2 and AA as 3 and the p-value for the

Hello, My R skills are somewhere between novice and intermediary, and I am hoping that some of you very helpful forum members, whom I've seen work your magic on other peoples' problems/questions, can help me here. I have a matrix with the following format: (i) individual plants comprising many different genotype groups (i.e., a plant is genotype 1 or genotype 2 or genotype 3, etc). The

Dear R users, I have a problem with something called "NaNs" in a nested mixed model. The background is that I have studied the number of insect nymphs emerging from replicated Willow genotypes in the field. I have 15 replicates each of 4 Willow genotypes belonging two 2 Willow species. Now I want to elucidate the effect of Willow genotype on the number of emerging nymphs. Previously I