similar to: warning message using lmer()?

I use lmer to fit a mixed effect model.It give some warnings.what does this warnings mean? and what should I do? > (fm2.mlm <- lmer(qd ~ edu + jiankang + peixun +hunyin + cadcj + age + age2 + sex + dangyuan + Comp.1 + Comp.2+trust.cz1 +(trust.cz1|commid), data = individual,na.action = "na.exclude",family="quasibinomial")) Generalized linear mixed model fit using PQL

Hello there, I am using nlme() to fit a logistic mixed effect model on our data. The outcome variable is binary. I got the error when I wanted to add a group factor to my model. My initial model is as below: model.a <- nlme(response~ 1/(1 + exp( -intercept- u0 - slope*TIME - u1*TIME)), + fixed=intercept+slope~1, random= u0+u1~1 |studentID,

Dear R users, I am trying to fit a GLMM to the following dataset; tab a b c 1 1 0.6 199320100313 2 1 0.8 199427100412 3 1 0.8 199427202112 4 1 0.2 199428100611 5 1 1.0 199428101011 6 1 0.8 199428101111 7 0 0.8 199527103011 8 1 0.6 199527200711 9 0 0.8 199527202411 10 0 0.6 199529100412 11 1 0.2 199626201111 12 2 0.8 199627200612 13 1 0.4 199628100111 14 1 0.8

I am working with mapping ActiveRecord onto a legacy database. All is going well (using set_table_name, set_primary_key, etc), but I can''t get my many<=>many relationships to work. My contrived example of the situation: Student has_and_belongs_to_many Teachers. This is mapped via table student2teacher where the foreign keys are studentId and teacherId. The primary key in Student

Dear all I want to compute Monte Carlo p-values in lmer-models based on sampled data sets. To speed up calculations, I've tried to use internal functions from the Matrix package (as suggested ealier on the list by Doug Bates). So I did: fm2 <- lmer(resistance ~ ET + position + (1|Grp), Semiconductor,method='ML') simdata<-simulate(fm2,nsim=1) ynew <- simdata[,1] mer

Hello, We are successfully using Samba with a remote WINS server which is located on another site. We have a second site (Worcester) which has successfully been using the same WINS server and communicating with our Samba servers (Shipley5 and Shipley6). Recently the PCs in Worcester have been unable to connect to our Samba server in Shipley. The other site uses a different DHCP server to our

Hi R-users: New to R and I am trying to run a GLM with random effects. I have 3 replicates ('Replicate) of counts of parasites ('nor.tot.lep') before and after an experiment ('In.Out'). When I run lmer I get the error messages (16 of each) below... > lmer(nor.tot.lep ~ In.Out + (In.Out|Replicate),data=coho, family =tweedie(var.power = 1, + link.power = 1)) Generalized

Hello all, I get the following and am not sure what is going on. Its on a solaris10 box. And my share is named 'hold' Thanks, Abhimanyu. # /opt/samba/bin/smbstatus Processing section "[hold]" Error loading module '/opt/samba/lib/charset/ISO8859-1.so': ld.so.1: smbstatus: fatal: /opt/samba/lib/charset/ISO8859-1.so: open failed: No such file

Hello everyone, I need to fit a bivariate normal regression model to a dataset where the same covariate (say, X) influences two separate but correlated responses (say, Y1 and Y2). So, the bivariate model would look like : Y1 = a1 + b1*X + e1 Y2 = a2 + b2*X + e2 where e1 and e2 are error terms which can be correlated. Is there any package in R which can help me fit this model ? Any help will be

Hello all, Simple version of my problem: I've got a list of data frames, where each data frame has the same number of columns and the same column names. I'd like to flatten the list into one large data frame. Is there an easy way to do this? Quick example code: a <- data.frame(x=c(1,2,3),y=c(5,7,9) b <- data.frame(x=c(2,4,7,9),y=c(2,3,5,4)) z <- list(a,b) # Do

Hi R-Users, I have 3 replicates ('Replicate) of counts of parasites ('nor.tot.lep') before and after an experiment ('In.Out'). I am trying to treat the three replicates as a random effect in order to determine if the main effect (In.Out) significantly influences my dependent variable (nor.tot.lep) after the variance explained by the replicates is accounted for. I have

Hi All, The data set that I have is a cluster data, and I want to run a HLM mixed model with multi-level response. Here is my data set: response: - Level (num: 1, 2, 3, 4, 5 - 5 levels) Covariates: - Type (Factor: A, B, C - 3 levels) - yr (num: 2006, 2007, ...) - Male (num: 0=not Male, 1=Male - 2 levels) - Ethnicity (Factor: A, B, H, ..., - 7 levels) - ELL (num: 0, 1, - 2

Hello I get the following errors: ./pdbedit Error loading module '/opt/samba/lib/charset/ISO8859-1.so': ld.so.1: pdbedit: fatal: /opt/samba/lib/charset/ISO8859-1.so: open failed: No such file or directory Any suggestions would be helpful. Abhimanyu Pandey Information Technologies Worcester State College Worcester, MA 01602 Office: 508-929-8913

> > If one compares the random effect estimates, in fact, one sees that > > they are in the correct proportion, with the expected signs. They are > > just approximately eight orders of magnitude too small. Is this a bug? > > BLUPs are essentially shrinkage estimates, where shrinkage is > determined with magnitude of variance. Lower variance more > shrinkage towards

Dear Sir, As per request below, I want to use your LLVM project in my thesis and I have no idea where to start and I couldn't find any information about how to build my test programs with your infrastructure and get my required information. Is your tool is a testing tool? Can it accept program and test case as input and output like the input test case is cover which branch and which

Hello all R-user I am relative new to the R-environment and also to GLMM, so please don't be irritated if some questions don't make sense. I am using R 2.0.0 on Windows 2000. I investigated the occurrence of insects (count) in different parts of different plants (plantid) and recorded as well some characteristics of the plant parts (e.g. thickness). It is an unbalanced design with 21

Hey- I''m using ROR 1.0 and script.aculo.us 1.5.1. I''ve been trying unsuccessfully to render a partial in a DIV, but can''t seem to get the right combination of stuff to make it work. There seems to be a few different ways of going about it. Right now I can render a partial. What do I need to to render the partial in a div? Here is what it looks like so far: #

I can't seem to find just what I'm looking for in R help, Everitt and Hothorn HSAUR, Murrell's book, or the R graphics gallery at http://addictedtor.free.fr/graphiques/. Probably not looking efficiently, but anyway, If my data look like this: > head(data) cat startyear studentid 1 other 2001 12 2 UHS 2001 17 3 Lourdes 2001 10 4

On starting an R session, I get the messages: Fatal errir: unable to restore save data in .RData Error in fun(...): couldn't find function "assignInNamespace" Error: .onLoad failed in 'loadNamespace' for 'Matrix' The only object in my .RData is last.warning, thus: > last.warning $"optim or nlminb returned message false convergence (8)"

Hi, I am trying to find the min of day for each student in each year. Here is the dataset: date studentid year 1/1/05 6:07 AM 236 20082009 3/27/09 9:45 AM 236 20082009 4/29/09 8:44 AM 236 20082009 3/27/09 11:36 AM 310 20082009 4/1/09 10:43 AM 310 20082009 10/15/09 8:54 AM 310