similar to: Fwd: modelling a nested student-school-district model in lmer

I'm helping a small grade school district convert to Samba servers, more specifically, replace the existing NT domain controllers. The district has 3 schools and about 1,700 students and staff members. There is one domain. Currently there are four NT4 DCs, a PDC and 3 BDCs, one in each school. The BDCs act as file servers. There are also several Linux machines running Samba as file

Hi, I was plotting or creating a map for Texas school districts using the shape file of Texas. I could not find any other helpful mail in the mailing list. txshp<-read.shape(system.file("S:\\Districts_10_11.shp", package="maptools")) Error- read.shape no found. But read.shape is there in maptools. If anyone can help me out it will be great. Thanks in advance. Shant

My school district will be building a new elementary school in 2006. We were about to go to bid with a traditional intercom system for the campus but I would like implement Asterisk at the campus. My question is, do we build in a traditional intercom/paging system and tie that into the Asterisk PBX, the way such intercoms have been connected to other PBX's in our district in the past, or

I am working on a project to unite several local school districts. We will have 14 different districts, every district would have their own asterisk box on location. We all have fiber lines running to a central location at our isd. This provides connectivity to all the districts. 1. would it be wiser to install a asterisk box at the central location of the ISD and have all asterisk boxes

suppose something like probability(passing test) is driven by 1. fixed effects -- sex 2. district effects - district funding 3. school effects - neighborhood income, racial composition, % two parent families, ... 4. class effects - teacher quality measurement, 5. individual random effects - IQ. how would such a model be setup in lmer? I can't find much discussion on the

Hi, Selon "Zhang, Xiantao" <xiantao.zhang at intel.com>: > >From 5f82ea88c095cf89cbae920944c05e578f35365f Mon Sep 17 00:00:00 2001 > From: Xiantao Zhang <xiantao.zhang at intel.com> > Date: Wed, 12 Mar 2008 14:48:09 +0800 > Subject: [PATCH] kvm/ia64: Add mmio decoder for kvm/ia64. [...] > + post_update = (inst.M5.i << 7) + inst.M5.imm7; > + if

For all School Employees Re: 50% Off Electronic Parts Company is offering a limited supply of top of the line brand new Laptop and Desktop computers to all School District teachers, staff and employees at 50% off MSRP. All Computers are brand-new packed in their original boxes and come with a full manufacturer's warranty plus ePC's 100% satisfaction guarantee. These computers are

good afternoon everyone! i am new to this list, so please forgive me for my ignorance. first, i have configured passwordless ssh to allow automatic trust between remote sites within the same internal network. i used the RSA keygen for that. secondly, i have a number of .dmg files kept on my master imaging server that need to be backed up off-site in the various schools around the district.

I have encountered a more fundamental problem in my data set. I''m using read.csv, and all the data are imported as character. How do I do a string comparison in a line like this: M10[ !sapply(1:10, function(x)666 %in% M10[x,]), ] Alternately, how do I change the class type on a column in a data frame from character to numeric? Thank you very much. Payam [[alternative HTML version

Hi to all the people again, I was writting a simply function in R, and wish to collect the results in a excel file. The work goes as follows, Ciervos<-function(K1, K0, A, R,M,Pi,Hembras) {B<-(K1-K0)/A T1<-(R*Pi*Hembras-M*Pi+B)/(Pi-M*Pi+R*Pi*Hembras) P1<-Pi-B R1<-P1*Hembras*R M1<-P1*M T2<-(R1-M1+B)/(P1-M1+R1) P2<-P1-B R2<-P2*Hembras*R M2<-P2*M

--T4sUOijqQbZv57TR Content-Type: text/plain; charset=us-ascii Content-Disposition: inline Dear R, I would like to report what I think is a bug in R. I am running R within emacs on a Digital AlphaStation. See the version information at the end of my R session for details. I also attach a copy of the file that is read in the `read.table' command. Here's my R session, with a few

I can't find a lot of information about using structures directly as parameters, returns, and in registers. Is this fully supported on all platforms? Does it always convert to creating a hidden parameter when too large? For example (assume very.large is too big to fit in the target machine registers): define %very.large @get_struct() { %m1 = insertvalue %very.large undef, i32 10, 0 ...

Dear all, dear Prof. Bates, my dependent variable (school absenteeism, truancy[1]) is a binary response for which I am trying to compute an unconditional mixed effects model. I've got observations (monday, wednesday and friday) nested in individuals (ID2), which were nested in classes (KID2) and schools (SID), i.e. a 4-level mixed effects model. In short, I was trying without success. I

Hi all, I am just starting my first models in R and am having trouble with some of the basics. The main things at the moment are about setting up my data correctly. I have a repeated measures design-all participants complete 4 experimental conditions. I want to fit a linear mixed effects model with crossed random effects for subject and item. I have 4 conditions, 6 items per condition. Because

Hi there, I've got a set of 10 numeric variables called Mood1 to Mood10 in a dataset called mood. I'm trying to create a set of 10 new variables called m1 to m10 so that m1=Mood1*1, m2=Mood2*2, etc to m10=Mood10*10 Trawling through the internet, I eventually tried the following code: for (i in 1:10){ assign(x=paste0("mood$m",i),

Dear R helpers,   Following is a R script I am using to run the Fast Fourier Transform. The csv files has 10 columns with titles m1, m2, m3 .....m10.     When I use the following commands, I am getting the required results. The probelm is if there are 100 columns, it is not wise to define 100 commands as fk <- ONS$mk and so on. Thus, I need some guidance to write the loop for the STEP A and

Hello! I would like to use lmer() to fit data, which are some estimates and their standard errors i.e kind of a "meta" analysis. I wonder if weights argument is the right one to use to include uncertainty (standard errors) of "data" into the model. I would like to use lmer(), since I would like to have a "freedom" in modeling, if this is at all possible. For

Hi, I am new to this list. I have a question regarding including both spatial and temporal random factors in lmer. These two are not nested, and an example of model I try to fit is model1<-lmer(Richness~Y+Canopy+Veg_cm+Treatment+(1|Site/Block/Plot)+(1|Year), family=poisson, REML=FALSE), where richness = integer Y & Treatment = factor Canopy & Veg_cm = numerical, continous

Hello all, Probably my concepts about the data.frame and matrix and array in R are not clear, I need some clarification to help me understand them better. >M <- read.table("test1.csv",sep=",",row.names=NULL,header=T) gives me: M as M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 1 9 11 14 15 18 20 20 20 20 20 2 3 4 8 9 11 12 14 15 15 15 3 4 5 8 8 9 9 9 9 9 9 4 4

Thanks to some help by Doug Bates (and the updated version of the Matrix package), I've refined my question about fitting nested and non-nested factors in lmer(). I can get it to work in linear regression but it crashes in logistic regression. Here's my example: # set up the predictors n.age <- 4 n.edu <- 4 n.rep <- 100 n.state <- 50 n <- n.age*n.edu*n.rep age.id