similar to: Question about data used to fit the mixed model

Hi everone, I have a question on using lme on a mixed effects model. The linear mixed model is in the form of: y = bX +Zu + e where "X" and "Z" are the matrices, "b" is the coefficient vector of fixed effects, "u" is the coefficient vector of random effects, and e is an error vector. I would like to use "lme" function to fit the model and

Paul: I may have found the issue (which is similar to your conclusion). I checked using egsingle in the mlmRev package as these individuals are strictly nested in this case: library(mlmRev) library(nlme) fm1 <- lme(math ~ year, random=~1|schoolid/childid, egsingle) fm2 <- lmer(math ~ year +(1|schoolid:childid) + (1|schoolid), egsingle) Checking the summary of both models, the output is

This question comes up periodically, probably enough to give it a proper thread and maybe point to this thread for reference (similar to the 'conservative anova' thread not too long ago). Moving from lme syntax, which is the function found in the nlme package, to lmer syntax (found in lme4) is not too difficult. It is probably useful to first explain what the differences are between the

Hi, I'm currently working on porting some SAS scripts to R, and hence need to do the same calculation (and get the same results) as SAS in order to make the transition easier for users of the script. In the script, I'm dealing with a two-factorial repeated-measures anova. I'll try to give you a short overview of the setup: - two between-cell factors: facBetweenROI (numbering

Dear ListeRs, I am trying to fit a heteroscedastic multilevel model using lmer{lme4- package). Take, for instance, the (fictive) model below. lmer(test.result ~ homework + Sex -1 + (1 | School)) Suppose that I suspect the error terms in the predicted values to differ between men and women (so, on the first level). In order to model this, I want the 'Sex'-variable to be random on

Dear List: I was able to run the following in nlme successfully, but the same model and code (same dataset) failed to run in lme4 and gave me the error message below. Any thoughts? lme(math~year, data=egsingle, random=~year|schoolid/childid) Error in lme(formula = math ~ year, data = egsingle, random = structure(list( : Unable to invert singular factor of downdated X'X

Hi all, I have a question regarding how to properly analyze a data set and then how to perform the analysis in R. First, I have data that I would like to analyze using a mixed GLM (I think this is the most appropriate method, but I am unsure). In a mixed model (y = X*beta+Z*gamma+epsilon), I would like to structure the variance matrices of gamma, G, and the error, R, to take advantage of all my

Hi, I was wondering if I might be able to ask some advice about doing residual plots for the lmer function in the lme4 package. Our group's aim is to find if the expression staining of a particular gene in a sample (or "core") is related to the pathology of the core. To do this, we used the lmer function to perform a logistic mixed model below. I apologise in advance

Hello, One of my users has a mailbox named 'INBOX.Kron & SPM' (maybe created a long time ago, when we use courier imap as pop/imap server, but I'm not sure). I can see the maildir with a doveadm list command: amateo_adm at myotis31:~$ sudo doveadm mailbox list -u <user> ... INBOX.Kron & SPM ... but I can't delete it, neithe rename it: amateo_adm at

Hello -- I posted this question yesterday and for some reason the post seems to be attached to the wrong thread. Also, I extended my test a little and it seems to indicate the problem is with spm. I would appreciate any help. Thanks. ========================================================== library(plyr) library(SemiPar) data <-

Hello, I am looking for a way to obtain standard errors for emprirical Bayes estimates of a model fitted with lmer (like the ones plotted on page 14 of the document available at http://www.eric.ed.gov/ERICDocs/data/ericdocs2/content_storage_01/0000000b/80/2b/b3/94.pdf). Harold Doran mentioned (http://tolstoy.newcastle.edu.au/~rking/R/help/05/08/10638.html) that the posterior modes' variances

Dear all, I am trying to plot on a spatial map the punctual measurements of the data located in the file (https://opengeo.metu.edu.tr/test.csv). I'd like to have the dots in some way proportional to the magnitudes of the measurements. I have difficulties with the code given below: The dot sizes do not vary not proportionally when varying the coefficient ("0.725"). It either plots

Suppose I have a mixed-effects model where yij is the jth sample for the ith subject: yij= beta0 + beta1(age) + beta2(age^2) + beta3(age^3) + beta4(IQ) + beta5(IQ^2) + beta6(age*IQ) + beta7(age^2*IQ) + beta8(age^3 *IQ) +random intercepti + eij In R how can I get an F test against the null hypothesis of beta6=beta7=beta8=0? In SAS I can run something like contrast age*IQ 1,

I'm hoping that this is a relatively easy question for someone familiar with the lme4 package. I'm accustomed to using HLM software and writing a simple 2 level [null] equation like this: L1 - Yij = b0 + e L2 - b0 = B00 + u0 The following command in R provides results that are identical to the HLM program. results <- lmer( Y ~ 1 |id , PanelData4) I can't

Hi all, Thanks to all who offered advice on using F95 in R. Now I'm trying to compile a test package using gfortran, Linux 2.4.21 and R 2.1.0. I was able to successfully compile and use a test F95 routine by setting my environment variables as follows in bash: export PATH=~/bin/:$PATH export F77=gfortran export LD_LIBRARY_PATH=~/bin/irun/lib export GFORTRAN_STDIN_UNIT=-1 Now I'm

The strip argument to panel.xyplot seems to be ignored for single-panel plots. Here is an example: data(Chem97, package = "mlmRev") myStrip <- function(...) { ltext(.5, .5, 'strip text') } densityplot(~ gcsescore, data = Chem97, strip=myStrip) The figure is printed with no strip. The strip.default documentation suggests that Deepayan intended this behavior.

Hi all, I have a data.frame with the following colnames pattern: x1 y11 x2 y21 y22 y23 x3 y31 y32 ... I.e. I have an x followed by a few y's. What I would like to do is turn this wide format into a tall format with two columns: "x", "y". The structure is that xi needs to be associated with yij (e.g. x1 should next to y11 and y12, x2 should be next to y21, y22, and

On 10 June 2017 at 21:04, biologi spm via llvm-dev <llvm-dev at lists.llvm.org> wrote: > clang.exe, clang++.exe, clang-cl.exe, clang-cl.exe and > msbuild-bin/cl.exe are each 37MB, but they serve almost the same > purpose, just receive different flavours of command flags. On Unix systems these are all symlinks and so essentially free. I hear Windows doesn't cope well with that

Hi all, Does anyone know how to report heteroskedasticity and autocorrelation-consistent standard errors when using the "spm" command in SemiPar package? Suppose the original command is sp1<-spm(y~x1+x2+f(x3), random=~1,group=id) Any suggestion would be greatly appreciated. Thanks, Susan [[alternative HTML version deleted]]

Hi, I'm running Centos 5.1 on an Intel Quad 2 Core with four Q6600 processors. Despite Centos 5 supporting multiple cores (SPM), it doesn't seem to work for me: 1) a dmesg shows that only one processor is seen: "SPM alternatives: switching to UP code", etc. 2) file /proc/cpuinfo shows only one processor 3) top with option 1 (to toggle between seeing all processors or an