similar to: problem with geepack

I have included data at the bottom of this email. It can be read in by highlighting the data and then using this command: dat <- read.table("clipboard", header = TRUE,sep="\t") I can obtain solutions with both of these: library(gee) fit.gee<-gee(score ~ chem + time, id=id, family=gaussian,corstr="exchangeable",data=dat) and library(yags) fit.yags <-

Dear all, I am trying to use the GEE methodology to fit a trend for the number of butterflies observed at several sites. In total, there are 66 sites, and 19 years for which observations might be available. However, only 326 observations are available (instead of 1254). For the time being, I ignore the large number of missing values, and the fact that GEE is only valid under MCAR. When I run the

I'm using the package geepack to fit GEE models. Does anyone know of methods for add1 and drop1 for a 'geeglm' model object, or perhaps a method for extractAIC based on the QIC of Pan 2001? I see there has been some mention of this on R-help a few years ago (RSiteSearch("QIC")). The package does provide an anova method for its model objects, and update() seems to work:

event.nab.2 is 0/1 and I dichotomized va to get va.2 to see if I could get geeglm to work. glm has no problem with the data but geeglm chokes. Each subject (patient.id) has at most 2 observations and more than 3/4 of the subjects have 2 observations. I have even worse problems trying to use glmmPQL from MASS and worse still trying to use lmer from lme4. But I figured a marginal model would work.

An embedded and charset-unspecified text was scrubbed... Name: not available URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20091126/7134fc17/attachment-0001.pl>

Hi, I downloaded both gee and geepack, and I am trying to understand the differences between the two libraries. I used the same data and estimated the same model, with a correlation structure autoregressive of order 1. Surprisingly for me, I found very different results. Coefficients are slightly different in value but sometimes opposite in sign. Moreover, the estimate of rho (correlation

Dear R users Recently I received advice from this fine group on gee() and sample weights One suggestion was to use geeglm() I hope someone can help me to solve a problem that arises when converting a code from gee to geeglm. *Here is a code that I wrote with the original data, not weighted: * > m1 <- gee( Bin ~ educ+agemean+ residencysize + yearx , id = rad09 , data = Males,

Dear R users, could you please help me figure out why I am getting an error? Initially my data looks like this: > attributes(compl)$names [1] "UserID" "compl_bin" "Sex.x" "PHQ_base" "PHQ_Surv1" "PHQ_Surv2" "PHQ_Surv3" [8] "PHQ_Surv4" "EFE"

Hi, having used both the gee pacakge and the geepack package, i am unsure of how to interpret the results. Here are the results from the geeglm function from the geepack package > gee2<-geeglm(data$erythema~data$product, data = data, id=subject, > family=binomial, corstr="independence") Warning message: In model.response(mf, "numeric") : using

Hi there, I just installed the package under windows, and it works very well. However, as I tried to install it on a cluster which uses linux OS, "Linux lionxc.aset.psu.edu 2.6.18-194.el5 #1 SMP Tue Mar 16 21:52:39 EDT 2010 x86_64 x86_64 x86_64 GNU/Linux" I always failed. The message during the installation process is as follows: > install.packages("geepack") Warning

Good evening, In my research I am studying the marginal models, where the main goal is on the structure of the association. My practical example has cluster with up to 600 observations and with this database, the function geese() return me the following message: This application has requested the runtime to terminate it is on unusual way. Please contact the application’s support team

Hi, In my research I am studying the marginal models, where the main goal is on the structure of the association. My practical example has cluster with up to 600 observations and with this database, the function geese() return me the following message: This application has requested the runtime to terminate it is on unusual way. Please contact the application’s support team for more

Hello, I have the following r-codes for solving a quasilikelihood estimating equation: >library(geepack) >fit<-geese(y~x1+x2+x3,jack=TRUE,id=id,scale.fix=TRUE,data=dat,mean.link = "logit", corstr="independence") Now my question is how can I calculate the confidence interval of the parameters of the above model "fit"? [[alternative HTML version deleted]]

I have a generalized linear model to solve. I used package "geepack". When I use the correlation structure "unstructured", I get a messeage that- R GUI front-end has stopped working. Why this happens? What is the solution? The r codes are as follows: a<-read.table("d:/bmt.txt",header=T")

Dear all, We have got data (response and predictor variables) for each country of the world; I started by fitting standard GLM and tested for spatial correlation using variogram models (geoR) fitted to the residuals of the GLM. Spatial autocorrelation is significant. Therefore, I think about using general estimation equations (geeglm or geese in geepack) allowing for residual spatial

This is no doubt trivial but after searching the help files and the web, I cannot seem to find it. 1) How do I convert 'hgt' into 'HGT' in R? 2) How should I have used the help facilities to find this? At the end of the day, all I want to do is case insensitive string matching... i.e. 'if ("HGT" == 'hgt') print('this should be true')' I tried

Hello, Is it possible to derive Pan's QIC (2001 Biometrics 57:120) from either a fitted gee() object in the gee package or from a geese() fit in the geepack package? If so, would anyone be kind enough to provide me with code to do so? I realize that QIC is part of the output from yags() but I would like to use one of the other functions. Thanks. Richard

Dear R users I am analysing data from a group of twins and their siblings. The measures that we are interested in are all correlated within families, with the correlations being stronger between twins than between non-twin siblings. The measures are all calculated from survey answers and by definition have limited ranges (e.g. -5 to +5), though within the range they are approximately normally

Dear R users, Could somebody tell me why the grey color ramp is repeated in this graph, eventhough the ramp values go from 0 to 1? I must be missing something obvious, but I can not see it! z <- c(0.064329041,0.117243316,0.161565116,0.19923015,0.231642175,0.259835539,0.284571226, 0.038507288,0.094184749,0.140959431,0.180803984,0.215159105,0.245096084,0.271412845,

Dear All, I have been trying to to do this for a few days now. I can generate persp plot OK and can generate it in colour using the command persp(x,y,z,col=terrain.colors(20)) However, I was wondering if it is possible to shade the 3d surface like a contour plot. i.e. black for large z, white for small z, say Thanks in advance Colin