similar to: Plackett-Dale Model in R

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

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]]

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)

Hello everybody, I would like to use the SpDep-package (especially the Local Moran index analysis and the Getis-Ord statistics) in R for analysing my data. However, I don't have x-y coordinates, but my data is in a distance matrix format. Is it possible to use the SpDep package with predefined distances as well instead of letting the program determining the distance itself by the function

Dear R-Users, Is it possible to get the covariance matrix from an lme model that did not converge ? I am doing a simulation which entails fitting linear mixed models, using a "for loop". Within each loop, i generate a new data set and analyze it using a mixed model. The loop stops When the "lme function" does not converge for a simulated dataset. I want to

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 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 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-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

My google search for Plackett's Algorithm didn't return too much except that Plackett's algorithm appears to be useful in Control Theory - it is elaborated as "Plackett's algorithm for on-line recursive least squares estimation". Sounds something like what I want. I am looking at developing a user modelling type app (new data points coming in and wanting to dynamically

Hello, Brand new user of R that I want to interface with Windew (http://www.pcsoft.fr), I am looking for a detailed documentation of R(D)Com. Does anybody know where I can find it, or do you have any form of experience of the use of R with Windev? Thanks for your help. PS : As I am new to the group, people interested in some details about the requestor could find his resume at address

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)+

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 forum,   I am working in R 2.9.1 and I am trying to sample locations from a network file. Reading in nor plotting is a problem, however when I am trying to sample from the file I get the following message:   nwlim<-readShapeLines("C:/Limburg_nwshape", proj4string=CRS("+init=epsg:31300")) plot(nwlim)   randacc<-spsample(nwlim,n=1000,"random")

Hi, It appears that there is no package for estimating log linear models (L. Goodman's family) for data in the form of frequency tables. Am I wrong? Thanks Marwan Khawaja Research Coordinator Fafo, Institute for Applied Social Science N-0608 Oslo, Norway Tel +47 22 08 86 00 +47 22 08 86 94 (Direct) +47 22 67 33 05 (Private) Fax +47 22 08 87 00

What is available to help design experiments with non-standard requirements? I have a recurring need to solve these kinds of problems, with deadlines of next Wednesday for two sample cases. The first of the two is "mission impossible", while the second is merely difficult. The following outlines briefly the two problems and the approach I'm currently considering. I'd

Hi all, Has anyone used the qua.regressCOP2 function from the copBasic package??? The default copula function used in this function is plackett copula and I wanted to use archimedean copula. Attached below is my code: mycop<-frankCopula V=seq(0.001,0.99,by=0.000217) R<-qua.regressCOP2(0.25,V,cop=mycop,para=c(3.504)) And this is the error I get: Warning messages: 1: In

Dear R-users, Is there an easy way to determine all possible vectors of length 21 with each entry having permutations from 0 to 4, instead of doing it like this? It really takes up too much time, and I am convinced that there exists something easier. Can you help me? Thank you in advance! Kind regards, Elke for (a in 0:4){ for (b in 0:4){ for (c in 0:4){ for (d in 0:4){