similar to: cross random effects (more information abuot the data)

Dear friends, I have asked last few days about cross-random effects using PQL, but I have not receive any answer because might my question was not clear. My question was about analysing the salamander mating data using PQL. This data contain cross-random effects for (male) and for (female). By opining MASS and lme library. I wrote this code sala.glmm <- glmmPQL(fixed=y~WSf*WSM,

Hi all - R2.0.1, OS X Perhaps while there is some discussion of lme going on..... I am trying to execute a glmm using glmmPQL from the MASS libray, using the example data set from McCullagh and Nelder's (1989, p442) table 14.4 (it happens to be the glmm example for GENSTAT as well). The data are binary, representing mating success (1,0) for crosses between males and females from two

Hi- I'm a biologist trying to figure out the growth rate of salamanders in different ponds. I collected individuals from various populations at different dates, and using the size and date collected, I want to figure out the growth curve of each population. My question is: How do I fit my data to a Gompertz function in R? Thank you so much! Sarah -- View this message in context:

I'm setting up a test server with a Digium TE122 and am getting the following error on the console, spewing as fast as it can. Does anyone have any idea what this error might be? [Oct 19 11:24:53] NOTICE[2076]: chan_dahdi.c:3108 my_handle_dchan_exception: PRI got event: Event 59 (59) on D-channel of span 2

Dear Sir/Miss: I'm very sorry to bother you,but I've found a bug in the Speex,Version 1.2beta1,and also I've have some questions. I'm deeply impressed by the work you have done in the coding and decoding of speech signal.But when using speex,I encoutered a bug,that is when in 32K mode,the window size is still 200 samples,but not 400 samples,the bug will bring the problem of

I am trying to understand my population abundance data and am looking into analyses of change point to try and determine, at approximately what point do populations begin to change (either decline or increasing). Can anyone offer suggestions on ways to go about this? I have looked into bcp and strucchange packages but am not completely convinced that these are appropriate for my data. Here is

Would anyone help me solve my problem with R, please? I am very new to R. I am doing logistic regression analysis on the presence/absence of salamanders using several predictor variables, as shown below. I have checked my data, but I didn't find any 'NA' or empty cells. When I used step() or stepAIC to select significant predictor variables, <none>s appear to places where

I have some questions regarding Zero Inflation Poisson models. I am using count data to analyze abundance trends of salamanders. However, I have surveys which differ in the amount of effort (i.e. the number of people searching and amount of time - I am using a museum database so not all surveys were conducted by me). Therefore I need to account for the effort. If change the count (response

Dear R helper, I hope that u can help me to sort out my problem because I sent an E-mail last night to R-list but I have not receive any help and at the same time I think this problem is not so hard. I have used the following functions before > K<-10 > prime<-c(2,3,5,7,11,13,17) > UN<-seq(1:K)%*%t(sqrt(prime)) > U1<-UN-as.integer(UN) > U<-matrix(qnorm(U1),K,7)

Hello R list, I am hoping to conduct a logistic regression with repeated measures, and would love an actual "code run through" for such an analysis. I found only one related post on this list, but a full answer was never provided. I understand that the routine lmer (or lmer2) in the lme4 package is often recommended in such a case, but actually implementing it is where I've hit a

Dear lmer users, The experiment includes 15 groups of (3 males and 1 female). The female is characterized by its quality Q1 and Q2. Each male of a group is characterized by the number of MatingAttempts (with Poisson distribution). I want to examine if male mating attempts depend on female quality. I can see from graphic exploration that the within-group heterogeneity of male attempts increases

Hi, I am attempting to plot survival curves estimated by cox proportional hazards regression model. The formula for the model is this: F.cox.weight <- coxph(Surv(Lifespan, Status) ~ MS + Weight + Laid + MS:Laid + Weight:Laid, data = LongF) MS = Mating status (mated/virgin) Weight = adult female weight, continuous covariate Laid = number of eggs laid by each female, continuous covariate I

On 19/09/2007, Daniel Aleksandersen <aleksandersen+xiphlists@runbox.com> wrote: > On Wednesday 19. September 2007 19:02:06 Ian Malone wrote: > > Daniel Aleksandersen wrote: > > > Attached is a much improved version of yesterday's draft. Introducing > > > the audio:collection:artwork element to deal with album cover graphics > > > and such. > >

WSO2 Web Services Framework For Ruby (WSF/Ruby) - 1.1.0 Released ======================================== WSO2 WSF/Ruby team is pleased to announce the release of WSO2 WSF/Ruby 1.1.0. WSF/Ruby is the Ruby language extension to WSO2 WSF/C. This enables you to consume/provide Web Services both with REST and with the power of WS-* stack including WS-Reliable Messaging, WS-Security, WS-Addressing and

I am a pretty new Wine user. I am hoping to be able to run some pretty large VBScript applications on it, to avoid porting them to Perl when we retire a Windows machine. All of our VBScript runs as children of a WSH ".wsf" file, for example as follows. I can get a simple ".vbs" file to run fine, but when I try to run the same file inside of a simple ".wsf" wrapper,

Thank you for contacting BizLand. We are working hard to ensure a smooth migration of shared-hosting customers from Website Factory to BizLand. We received your message on 8/20/02 at 12:54:32 AM regarding your e-mail titled: Re: [vorbis] Partial Format converters?. Your message has been assigned a tracking number of T20020820004D. Should you need to contact us regarding your original message,

I have been using lme from nlme to do a 3-way anova with all the effects treated as random. I was wondering if someone could direct me to an example of how to do this using lmer from lme4. I have 3 main effects, tim, trt, ctr, and all the interaction effects tim*trt*ctr. The response variable is ge. Here is my lme code: dat <-

Hi there, I am reading the 2004 paper "Smoothing with mixed model software" in Journal of Statistical Software, by Ngo and Wand. I tried to run their first example in Section 2.1 using R but I had some problems. Here is the code: library(nlme) fossil <- read.table("fossil.dat",header=T) x <- fossil$age y <- 100000*fossil$strontium.ratio knots <-

Hi, I have a data set on germination and plant growth with the following variables: dataset=fm mass (response) sub (fixed effect) moist (fixed effect) pop (fixed effect) mum (random effect nested within population) iheight (covariate) plot (random effect- whole plot factor for split-plot design). I want to see if moist or sub interacts with mum for any of the pops, but I am getting an error

Hi R helpers, I'm trying to fit a rather complex model to some simulated data using lme and am not getting the correct results. It seems there might be some identifiability issues that could possibly be dealt with by specifying starting parameters - but I can't see how to do this. I'm comparing results from R to those got when using GenStat... The raw data are available on the