similar to: Help with lme code

Dear R - Users I have some problems fitting a linear mixed effects model using the lme function (nlme library). A sample data is as shown at the bottom of this mail. I fit my linear mixed model using the following R code: bmr <-lme (outcome~ -1 + as.factor(endpoint)+ as.factor(endpoint):trt, data=datt, random=~-1 + as.factor(endpoint) + as.factor(endpoint):trt|as.factor(Trial),

Dear R-users I am relatively new to R, i hope my many novice questions are welcome. I have problems accessing some objects (specifically the random effects, correlation structure and variance function) from an object of class gls and lme. I used the following models: yah <- gls (outcome~ -1 + as.factor(Trial):as.factor(endpoint)+

Hello R-users I am new to R and trying to write some functions. I have problems writing functions that takes a data set as an arguement and uses variables in the data. I illustrate my problem with a small example below: sample data #------------------ visual24<-rnorm(30,3,5) visual52<-rt(30,7) dats<- data.frame(cbind(visual24,visual52)) remove(visual24, visual52)

Dear R-users I have problems using lme The model i want to fit can be viewed as a two-level bivariate model Two-level bivariate: bivariate (S coded as -1,T coded as 1) endpoint within trial OR It can equivalently be considered as a three-level model.Three-level: endpoint within patient, patient within trial. My code tries to model the levels through a RANDOM statement and a

Dear R-helpers, We marked 6000 leaves from 5 SPECIES - 10 individuals/species - in two different TREATMENTs: a control and a dry-plot from which 50% of incoming precipitation was excluded. We followed those leaves for 42 months and noted the presence and absence at each visit. I then carried out a Cox Harzard model to see differences in leaf mortality between parcels and among species over time:

Dear R Users I have difficulties accessing the variance components for an lme fit when the variance covariance matrix of the random effects is not positive definite. Can anyone inform me on how to get by this ? Thanks in advance Pryseley --------------------------------- [[alternative HTML version deleted]]

Good day R-Users, I have a problem accessing some values in the output from the summary of an lme fit. The structure of my data is as shown below (I have attached a copy of the full data). id trials endp Z.sas ST 1 1 -1 -1 42.42884 1 1 1 -1 48.12007 2 1 -1 -1 43.42878 2 1 1 -1

I am using the sink function to save several results (i.e. values of many different variables) to an output file. However, the output looks unattractive because it displays line numbers next to each new variable, it is difficult to remove the R variable name from the output, and I cannot print test without it using quotation marks. The only way I have found around most of these issues is to

Not as smooth an experience as I had assumed it would be after a test run with a clean install worked perfectly. So figured I would share the experience in case anybody else runs into similar situation since not all information are consolidated in a single place. Physical machine in question is a 4yr W2008R2 server (non-raided!) running custom app from defunct developer which is why I am

-----Original Message----- From: CentOS [mailto:centos-bounces at centos.org] On Behalf Of Nicolas Kovacs Sent: Sunday, December 17, 2017 12:52 PM To: centos at centos.org Subject: Re: [CentOS] Offsite hosted backup solutions > Can't say about Windows clients, but for all my Linux machines, I'm Hands down Veeam Endpoint Backup for Windows clients to a secure samba share.

We installed BMR boot server version 6.0 on DELL server. This DELL server have CENTOS 3.7 in it. We got error message when we tried to use "bmrsrtadm". Anyone know how to fix it or work around? ./bmrsrtadm Select one of the following options: 1. Create a new Shared Resource Tree. 2. Create a new CD image based Shared Resource Tree. 3. Copy an existing

A few questions: 1. How does ZFS compare to Luster? 2. Is ZFS compatible with Veritas Netbackup Suite? 3. Does ZFS support bare metal restore (BMR)? Pointers welcome!! Gary -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://mail.opensolaris.org/pipermail/zfs-discuss/attachments/20060214/328c6cc4/attachment.html>

Hi, I have inherited a Samba PDC running on SuSE Linux Enterprise Server 10.1 (the Samba version is 3.0.24-2.23-1296-SUSE-CODE10). The server has been giving problems for a few weeks including the following symptoms: 1. Users accessing a share are experiencing intermittent problems writing to the share (Excel tells them the file they are trying to write is read-only). 2. when I try to add a

Dear R-Users I used the nlme library to fit a linear mixed model (lme). The random effect standard errors and correlation reported are based on a Log-Cholesky parametrization. Can anyone tell me how to get the Covariance matrix of the random effects, given the above mentioned parameters based on the Log-Cholesky parametrization?? Thanks in advance Pryseley

Hello R-users Is it possible to fit a three level linear mixed effect model in R? If anyone has an idea or sample code, i will appreciate it very much if i can receive it. I am reading the book by Pinheiro and Bates but have not come across that yet! Kind regards Pryseley --------------------------------- [[alternative HTML version deleted]]

Dear R-users Can anyone inform me of a library or more specifically functions that can maximise (or calculate) a Pairwsie likelihood from a data. Better still, i would like to know if there is a function (library) that fits regression models based on pairwise likelihoods. Thanks Pryseley --------------------------------- [[alternative HTML version deleted]]

Dear R users, Can someone inform me about a library/function in R that fits a Plackett-Dale model ? Thanks in advance Pryseley --------------------------------- [[alternative HTML version deleted]]

Dear R-Users I have a problem accessing some values in the output from the summary of an lme fit. I fit the model below: ggg <- lme (ST~ -1 + as.factor(endp):Z.sas + as.factor(endp), data=dat4a, random=~-1 + as.factor(endp) + as.factor(endp):Z.sas|as.factor(trials), correlation = corSymm(form=~1|as.factor(trials)/as.factor(id)), weights=varIdent(form=~1|endp)) hh

Dear R-users I intend to create a function which calls some smaller other functions in return. Some of these smaller functions all call some functions. I do not know a good way to do this. I tried using the source() function to include the smaller functions within the main functions before they are called. This does not work, or maybe i am not doing the right thing. For example: the

Dear all, I am trying to fit a model with crossed random effects using lme. In this experiment, I have been measuring oxygen consumption (mlmin) in bird nestlings, originating from three different treatments (treat), in a respirometer with 7 different channels (ch). I have also measured body mass (mass) for these birds. id nest treat year mlmin mass ch hack 1EP51711 17