similar to: how to obtain "par(ask=TRUE)" with trellis-plots

Dear list members, the following hlm was constructed: hlm <- groupedData(laut ~ design | grpzugeh, data = imp.not.I) the grouped data object is located at and can be downloaded: www.anicca-vijja.de/lg/hlm_example.Rdata The following works: library(nlme) summary( fitlme <- lme(hlm) ) with output: ... AIC BIC logLik 425.3768 465.6087 -197.6884 Random effects:

Dear altogether, is it possible to integrate "weights" arguments within lmer to incorporate statements to handle heteroscedasticity as it is possible with lme? I searched the R-archive but found nothing, insofer I assume it is not possible, but as lmer is under heavy develpoment, maybe something changed or is solved differently. Thus my question: While encountering heavy

Dear alltogether, I am searching for a way to determine "effect size" in multi-level models by using lme(). Coming from Psychology, for ordinary OLS there are measures (for meta-analysis, etc.) like CohensD <- (mean_EG - mean_CG) / SD_pooled or (p)eta^2 <- SS_effect / (SS_effect + SS_error) I do not intend to lead a discussion of the usefulness of such measures as long as

Dear alltogether, I experience very strange behavior of imputation of NA's with the NORM library. I use R 2.2.0, win32. The code is below and the same dataset was also tried with MICE and aregImpute() from HMISC _without_ any problem. The problem is as follows: (1) using the whole dataset results in very strange imputations - values far beyond the maximum of the respective column, >

Hi all, does anyone know how to automatically update starting values in R? I' m fitting multiple nonlinear models and would like to know how I can update starting values without having to type them in. thank all --- On Fri, 12/26/08, r-help-request@r-project.org <r-help-request@r-project.org> wrote: From: r-help-request@r-project.org <r-help-request@r-project.org> Subject:

Dear alltogether, two lme's, the data are available at: http://www.anicca-vijja.de/lg/hlm3_nachw.Rdata explanations of the data: nachw = post hox knowledge tests over 6 measure time points (= equally spaced) zeitn = time points (n = 6) subgr = small learning groups (n = 28) gru = 4 different groups = treatment factor levels: time (=zeitn) (n=6) within subject (n=4) within smallgroups

Hi all: I am a user of "JM" package. Here's the problem of "sample size". The warning is: Error in jointModel(fitLME, fitSURV_death, timeVar = "time", method = "piecewise-PH-GH") : sample sizes in the longitudinal and event processes differ. According to the suggestion of "missing data",I use the same data set(data_JM) without any

Dear altogether, I tried local regression with the following data. These data are a part of a bigger dataset for which loess is no problem. However, the plot shows extreme values and by looking into the fits, it reveals very extreme values (up to 20000 !) although the original data are > summary(cbind(x,y)) x y Min. :1.800 Min. :2.000 1st Qu.:2.550

I contacted the package developer and that lead to me removing events at time 0 (or subjects with only 1 longitudinal measurement). I then still had the error message "Can't fit a Cox model with 0 failures" which I have managed to avoid by adding 1.8*10^(-15) to all my survival times, any number greater than this also works but nothing smaller! Any explanation of this would help!

Hello All, While trying to install Matrix package following error message came out: /usr/bin/ld: cannot find -lblas-3 collect2: ld returned 1 exit status make: *** [Matrix.so] Error 1 ERROR: compilation failed for package 'Matrix' ** Removing '/usr/lib/R/library/Matrix' ** Restoring previous '/usr/lib/R/library/Matrix' It seems that someting is missing. Have anybody

I have used LME to fit a mixed effects model on my data. The data has 274 subjects with 1 to 6 observations per subject. Time is not linearly associated with the outcome, so I used ns to fit a natural cubic spline with 3 auto knots. Subject and the natural cubic time of spline are both treated as random effects. This model has run without any problem, but now I would like to plot trajectories for

Hello alltogether, how is it possible to assign the colnames of a data.frame to a function called by apply, e.g. for labeling a plot? Example: I want to plot several qqnorm-plots side by side and there should be a maintitle for each qqnorm-plot which is identical to the respective colname. I checked, but the column which is processed by the function called by apply does not contain a colname

Dear R-list, I try to transform a mathematica script to R. #######relevant part of the Mathematica script (* p_sv *) dd = NN (DsD - DD^2); lownum = NN (L-DD)^2; upnum = NN (H-DD)^2; low = lownum/(2s^2); up = upnum/(2s^2); psv = NIntegrate[1/(s^NN) Exp[-dd/(2s^2)] (Gamma[1/2,0,up] + Gamma[1/2,0,low]),{s,sL,sH}, MinRecursion->3]; PSV = psv/Sqrt[2NN]; Print["------------- Results

Hi, I am trying to extract the coefficients matrix from a gls summary. Contrary to the lm function, the command fit$coefficients returns only the estimates of the model, not the whole matrix including the std errors, the t and the p values. example: ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14) trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69) group <-

Hi, Can you please help me with this please? What I am trying to do is call a vector from R function and used in the new function So I create 4 functions with these arguments M11 <- function(TrainData,TestData,mdat,nsam) { ls <- list() I have few statments one of them is vectx <- c(,1,2,3,4,5,6,6) vectz <- c(12,34,5,6,78,9,90) and then................ ls(vectx=vtecx,vectz=vectz)

Hello, I am analyzing some climate time series data using the Mann Kendall package and was wondering if there was a way to calculate the trend using Sen's nonparametric estimator slope in R? Thank you in advance, Barry _________________________ Barry Baker, Ph.D. Global Climate Change Initiative The Nature Conservancy 2424 Spruce St., Suite 100 Boulder, CO 80302 Tel: (303)-541-0322 Fax:

Hello list, I have an Asterisk setup with the following details: 1. 3 x internal extensions / sip hardphones - Grandstream 2000 2. 2 x internal extensions / dahdi cordless phone 3. 1 x 2 FSX ports OpenVOX pci card 4. 1 x internal sip extension / sip softphone (linphone) 5. 1 x 800Mhz Asterisk + Linux server 6. Asterisk version is 1.6.2.13 7. 1 x IAX2 incoming trunk from phone provider for 1

Hello, I've added a samba4 as a second DC in a network where the first DC is a Win2k8R2. The join seems to run smoothly. But after the join an ldapsearch -LLL -x -H ldapi://%2Fvar%2Flib%2Fsamba%2Fprivate%2Fldap_priv%2Fldapi on the samba, return some strage things: ? some attributes like unicodePwd and supplementalCredentials are missing ? lots of attributes are base64 encode (ex: memberOf::

Dear all, I am trying to write a function for visualizing ordinal model results. The function works fine with some values, but then I get "Error: subscript out of bounds" even there the index should be pointing a legal item. Code is below as well as the example of failure: plotProb <- function(pre.mat, parts, split, titles, xlab="") { par(mfrow = split) n <- 1

Hi, I am fitting a weighted least square regression and trying to compute SSE,SST and SSReg but I am not getting SST = SSReg + SSE and I dont know what I am coding wrong. Can you help please? xnam <-colnames(X) # colnames Design Matrix fmla1 <- as.formula(paste("Y ~",paste(xnam, collapse=