similar to: R lmer with problem of 'sd slot has negative entries'

R Users, Emine Bayman sent this out earlier and we do not think it went through. Appologies if it did. We want to fit GLMM with lmer with binomial data and a one-way random effects model (overall mean is a fixed effect and there are random effects for each binomial). We are using the Laplace method. We are simulating multiple data sets and use the Laplace method with control = list

Dear R users, I'm pretty new on using lmer package. My response is binary and I have fixed treatment effect (2 treatments) and random center effect (7 centers). I want to test the effect of treatment by fitting 2 models: Model 1: center effect (random) only Model 2: trt (fixed) + center (random) + trt*center interaction. Then, I want to compare these 2 models with Likelihood Ratio Test.

It's easier to get it to other places if it starts out in the configure script. Also split the list into language and non-language plugins. --- common-rules.mk | 44 ---------------------------------------- configure.ac | 53 +++++++++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 53 insertions(+), 44 deletions(-) diff --git a/common-rules.mk b/common-rules.mk index

Dear list I try to run a bootstrap with lmer. I often, but not always, get the error message: Error in objective(.par, ...) : Leading minor of order 6 in downdated X'X is not positive definite (with the number (here 6) varying) In R-archives I came across some threads that treated this problem, nevertheless they refer to lmer when using it with family = "binomial", so the

Bizarre uptick in the amount of XML reported by Ohloh here: http://www.ohloh.net/p/libguestfs/analyses/latest Which in one sense is true. We added some example XML output from virt-inspector to the repository: $ find -name '*.xml'|xargs wc -l 6822 ./inspector/example1.xml 7323 ./inspector/example2.xml 577 ./inspector/example3.xml 17 ./inspector/example4.xml

Hi all, I've now got a problem with some modified lmer code (function lmer1 pasted at end) - I've made only three changes to the lmer code (marked), and I'm not really looking for comments on this function, but would like to know why execution of the following commands that use it almost invariably (but not quite predictably) leads to the R session terminating. Here's the command

Hi, I am using lmer to analyze habitat selection in wolverines using the following model: (me.fit.of <- lmer(USED~1+STEP+ALT+ALT2+relM+relM:ALT+(1|ID)+(1|ID:TRKPT2),data=vdata, control=list(usePQL=TRUE),family=poisson,method="Laplace")) Here, the habitat selection is calaculated using a so-called discrete choice model where each used location has a certain number of alternatives

consider p as random effect with 5 levels, what is difference between these two models? > p5.random.p <- lmer(Y ~p+(1|p),data=p5,family=binomial,control=list(usePQL=FALSE,msV=1)) > p5.random.p1 <- lmer(Y ~1+(1|p),data=p5,family=binomial,control=list(usePQL=FALSE,msV=1)) thanks, Aimin Yan

consider p as random effect with 5 levels, what is difference between these two models? > p5.random.p <- lmer(Y ~p+(1|p),data=p5,family=binomial,control=list(usePQL=FALSE,msV=1)) > p5.random.p1 <- lmer(Y ~1+(1|p),data=p5,family=binomial,control=list(usePQL=FALSE,msV=1)) in addtion, I try these two models, it seems they are same. what is the difference between these two model. Is

On Sun, Jun 28, 2020 at 4:03 PM Richard W.M. Jones <rjones@redhat.com> wrote: ... > + > +static int > +tar_get_ready (void) > +{ > + FILE *fp; > + CLEANUP_FREE char *cmd = NULL; > + size_t len = 0; > + bool scanned_ok; > + char s[256]; > + > + /* Construct the tar command to examine the tar file. */ > + fp = open_memstream (&cmd, &len); >

Allow a plugin field to declare whether a parallel plugin can tolerate windows where fds are not CLOEXEC, or must take precautions to avoid leaking fds if the plugin may fork. For safety reasons, the flag defaults to off, but many in-tree plugins can set it to on (most commonly because they don't fork after .config_complete; for libvirt because it is documented to clean up fds on fork so it

Respected Sir, With reference to my mail to you and the reply mail by you dated 9th and 16th January, 2013, I am sending the reproducible code in the attached document named " MODIFIED ANS ". I am also attaching the txt file named "hazModel", which is required to save in my documents folder to run the program. The file also contains the error message

Hi all, I am currently doing a consistency analysis using an lmer model and trying to use parametric bootstrapping for the confidence intervals. My model is like this: model<-lmer(y~A+B+(1|C/D)+(1|E),binomial) where E is the individual level for consistency analysis, A-D are other fixed and random effects that I have to control for. Following Nakagawa and Scheilzeth I can work out the

Following the recommendation of Prof. Ripley, I have created the Makevars file with the line: PKG_LIBS="-L/usr/lib/libm -lm -L/usr/local/lib/libgsl -lgsl -L/usr/local/lib /libgslcblas -lgslcblas" in the working directory. Now I have the code file Example3.c which computes the Bessel function value (the example is taken from the GSL reference book). I am running: R CMD SHLIB Example3.c

Hello, I would appreciate *any* ideas on this problem. I'm the maintainer of a package ("subselect"), which on CRAN's Daily Package Checks is OK on all flavours of R, except r-devel Linux x86_64, where there is a "memory not mapped" segfault with the very first example that is tried out (output below). Additionally, a user with an AMD64 machine has just reported a

--- plugins/tar/{tar.pl => nbdkit-tar-plugin.pod} | 145 ++------- configure.ac | 2 - plugins/tar/Makefile.am | 41 +-- tests/Makefile.am | 14 +- plugins/tar/tar.c | 286 ++++++++++++++++++ tests/test-dump-plugin.sh | 2 +- tests/test-help-plugin.sh

Dear all, I am trying to use the function odfWeave. Unfortunately I cannot get beyond the folllowing error message: " Error in odfWeave("Example3.rnw", "Example3.odf") : Error unzipping odt file " Can anybody tell me, how to use this function? Thanks, Irina Ursachi.

Hello, I am trying to do contrasts after applying a binomial mixed effect model with the function lmer. I have to extract the fix effect values, but as I write fixef(model), I get this error message: Error in UseMethod("fixef") : no method for 'fixef' with objects of class "mer" Has anybody some ideas why? And how can I then post-hoc testing my data if I cannot do

I am having a problem extracting from "mer" objects.    I have constructed my problem using existing datasets.   Using the following commands:   require(lme4) fm1 <- lmer(Yield ~ 1 + (1 | Batch), Dyestuff) fixef(fm1) I get the following error message: "Error in UseMethod("fixef") : no applicable method for "fixef""   I know that "fixef" is in

R-experts: In 2002, Hans Van Houwelingen et al. published a tutorial on how to do meta-regression in Statistics in Medicine. They used the classic BCG dataset of Colditz to demonstrate correct methodology and computed the results using PROC MIXED in SAS. In trying to duplicate the results presented in this paper, I have discovered that I can reproduce certain items with lmer but not