similar to: Corstr in the Gee (Generalized Estimation Equation) arguments?

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Dear all, I am working on modifying the R working matrix to commodate some other correlations that not included in the package. I am having problem to locate where the R matrix are defined for regular matrices, i.e. independence, exchangeable, AR and unstructure. it might have something within .C("Cgee",but don't understand it well enough to know. Can you anyone help? /*gee source

Hello, Is there a simple way of stacking/merging two dataframes in R? I want to stack them piece-wise, not simply add one whole dataframe to the bottom of the other. I want to create as follows: x.frame: aX1 bX1 cX1 ... zX1 aX2 bX2 cX2 ... zX2 ... ... ... ... ... aX99 bX99 cX99 ... zX99 y.frame: aY1 bY1 cY1 ... zY1 aY2 bY2 cY2 ... zY2 ... ... ... ... ... aY99 bY99 cY99 ...

Hi, How to perform a stepwise selection of the best models for gee? Why can't step() do this job? Thanks. Sincerely Yours, Jinn-Yuh Guh, M.D. Dept. of Internal Medicine Kaohsiung Medical College 100 Shi-Chuan 1st Road Kaohsiung, Taiwan FAX: 886-7-312-2810 e-mail: jyuh at mail.nsysu.edu.tw -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hi all, 1. Can nonlinear models be used in gee? For example, I have a dataset which contains 2 variables x and y, I wrote data(ex) atttach(ex) a<-100 b<- -0.5 c<-4.5 d<-20 Then: a. y~gee(y~d+(a-d)/(1+(x/c)^b)) Error in terms.formula(formula, data = data) : invalid power in formula b. y~gee(y~d+(a-d)/(1+(x/c)) Error in model.frame(formula, rownames, variables, varnames, extras,

Dear all, I need to fit a gee model with an auto-regressive correlation structure and I faced some problems. I attach a simple example: ####################################################### library(gee) library(geepack) # I SIMULATE DATA FROM POISSON DISTRIBUTION, 10 OBS FOR EACH OF 50 GROUPS set.seed(1) y <- rpois(500,50) x <- rnorm(500) id <- rep(1:50,each=10) # EXAMPLES FOR

Hi, I'm trying to figure out if there are any packages allowing one to fit mixed models (or non-linear mixed models) to data that includes censoring. I've done some searching already on CRAN and through the mailing list archives, but haven't discovered anything. Since I may well have done a poor job searching I thought I'd ask here prior to giving up. I understand that

I have a program which is doing a few thousand runs of lm(). Suppose it is a simple model y = a + bx1 + cx2 + e I have the R object "d" where d <- summary(lm(y ~ x1 + x2)) I would like to obtain Var(x2) out of "d". How might I do it? I can, of course, always do sd(x2). But it would be much more convenient if I could snoop around the contents of summary.lm and

Hei Group, I want to compare the relative importance of predictors in a multiple linear regression y~a+bx1+cx2... However, bptest indicates heteroskedasticity of my model. I therefore perform a robust regression (rlm), in combination with bootstrapping (as outlined in J. Fox, Bootstrapping Regression Models). Now I want to compare the relative importance of my predictors. Can I rely on the

hi all- I am doing some research, have never used R before until today and need to understand the following program for a project. if some one could PLEASE help me understand this program ASAP i would GREATLY appreciate it (any syntax/ statistic comments would be great) PLEASE PLEASE HELP!! THANKYOU!!! -on a side note, it seems to me that R doesnt include the pv, and it was calculated

Dear all, I'm confused by the time serie parameters in data(lh) : sueoka:~ lobry$ R --vanilla --quiet > tsp(lh) [1] 1 48 1 because documentation says: QUOTE A regular time series giving the luteinizing hormone in blood samples at 10 mins intervals from a human female, 48 samples. UNQUOTE So that I would expect the time serie to end at 480 minutes or 8 hours. Shouldn't we have

Dear all R users, I have a small doubt about panel data analysis. My basic understanding on Panel data is a type of data that is collected over time and subjects. Vector Autoregressive Model (VAR) model used on this type of data. Therefore can I say that, one of statistical tools used for analysis of panel data is VAR model? If you clarify my doubt I will be very grateful. Thanks and regards,

Hi - The problem is with two abline(s). Attached are: 1) jnk.r to run program 2) jnk.rin the data 3) jnkps.eps the postscript output 4) jnkscreen.bmp (from photoshop after bmp copy to clipboard) in jnk.zip the eps and bmp are different on my machine (windows 2000) any suggestions appreciated bob >>> Diego.Kuonen at epfl.ch 03/18/00 08:24AM >>> "Robert L.

Hi, I am far from experienced in both R and time series hence the question. The code for spec.pgram() seems to involve a circularity of the kernel (see below) yielding new power estimates to all frequencies computed by FFT. " if (!is.null(kernel)) { for (i in 1:ncol(x)) for (j in 1:ncol(x)) pgram[, i, j] <- kernapply(pgram[, i, j], kernel, circular = TRUE)

Hello I try to find probability values of some predictor combinations using logistic reg. in response level. Firstly I found coefficients by glm function. Then I followed two ways to get probability values: 1- probility <- exp(X0+bX1+cX2+...)/((1+exp(X0+bX1+cX2+...)) 2- probility <- predict(glm.obj,type="resp") Should have these two given same result ? if so, I did not have. Why

Hi there, Just wondering if anyone has any tips for using arrays? I am trying to convert the following SAS code to R: data A2; set A1; by subject_id; retain BX1-BX10 i; array b(1:10) BX1-BX10 ; if first.subject_id then do ; do j=1 to 10; b(j) = .; end; i=1; end; b(i) = BX; i = i+1; if last.subject_id then

Hi, Suppose I've got a matrix, and the first few elements look like "x1 + x3 + x4 + x5 + x1:x3 + x1:x4" "x1 + x2 + x3 + x5 + x1:x2 + x1:x5" "x1 + x3 + x4 + x5 + x1:x3 + x1:x5" and so on (have got terms from x1 ~ x14). If I want to replace all the x1 with i7, all x2 with i14, all x3 with i13, for example. Is there an easy way? I tried to put what I want

Hi, Are there some texts about time series that teatches it with R? And site 'bout time series "for dummies" , can anyone indicate them for me? thanks a lot Rafael Bertola Undergraduate in Statistics at UNICAMP - Brasil -------------------------------------------------- --------------------------------------------------

Hi, (R version 2.15.0) I am running a pgm with 1 response (earlier standardized Y) and 44 independent vars (Xi) from the same data =a2: When I run the 'lm' function on single Xi at a time, the beta coefficient for let's say X1 is = -0.08 (se=0.03256) But when I run the same Y with 44 Xi-s with the 'step' function (because I left direction parameter empty, I assume a backward

Hao Yu Commercial Scale Out IBM T.J. Watson Research Center 1101 Kitchawan Rd/Route 134, Rm 36-019 Yorktown Heights, NY 10598-0218 914-945-1854, Email: yuh@us.ibm.com ----- Forwarded by Hao Yu/Watson/IBM on 10/31/2006 09:52 AM ----- Jimi