similar to: lme4 and false convergence

Hi All, I am trying to shift from running mixed models in SAS using PROC MIXED to using lme4 package in R. In trying to match the coefficients of R output to that of SAS output, I came across this problem. The dataset I am using is this one: http://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_mixed_sect034.htm If I run the following code: proc mixed data=rc

This replaces find_vq/del_vq with find_vqs/del_vqs virtio operations, and updates all drivers. This is needed for MSI support, because MSI needs to know the total number of vectors upfront. Signed-off-by: Michael S. Tsirkin <mst at redhat.com> --- drivers/block/virtio_blk.c | 11 +++--- drivers/char/hw_random/virtio-rng.c | 11 +++--- drivers/char/virtio_console.c | 27

This replaces find_vq/del_vq with find_vqs/del_vqs virtio operations, and updates all drivers. This is needed for MSI support, because MSI needs to know the total number of vectors upfront. Signed-off-by: Michael S. Tsirkin <mst at redhat.com> --- drivers/block/virtio_blk.c | 11 +++--- drivers/char/hw_random/virtio-rng.c | 11 +++--- drivers/char/virtio_console.c | 27

Hello, I hope that you can bare with me. I am new to models, but I think I have a pretty godd understanding of how to run them now, including how to use AICc and Anova. The issue is that I have many factors that I wish to compare so doing each one at a time would take forever. I came across the MuMIn package and I was so excited, however I am getting an error message and i don't know why.

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

On 06/22/2017 08:06 AM, Peter Rosin wrote: > The redundant fb helper .load_lut is no longer used, and can not > work right without also providing the fb helpers .gamma_set and > .gamma_get thus rendering the code in this driver suspect. > Hi Peter, STM32 chipsets supports 8-bit CLUT mode but this driver version does not support it "yet" (final patch has not been upstreamed

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

Call drm_mode_size_dumb() to compute dumb-buffer scanline pitch and buffer size. Align the pitch according to hardware requirements. Signed-off-by: Thomas Zimmermann <tzimmermann at suse.de> Cc: Sui Jingfeng <suijingfeng at loongson.cn> Cc: Sui Jingfeng <sui.jingfeng at linux.dev> --- drivers/gpu/drm/loongson/lsdc_gem.c | 29 ++++++++--------------------- 1 file changed, 8

Hello, I've run 7 candidate models using mixed-effects logistic regression with the lmer function from the lme4 package, and I'm getting the following error for 5 of those models: Warning message: In mer_finalize(ans : false convergence (8). The candidate models all run with the same data, just slightly different formulas (for AIC model selection). Can anyone explain this error to

Dear all, For a project I need to calculate the conditional AIC of a mixed effects model. Luckily, I found a reference in the R help forum for a function to be used: CAIC <- function(model) { sigma <- attr(VarCorr(model), 'sc') observed <- attr(model, 'y') predicted <- fitted(model) cond.loglik <- sum(dnorm(observed,

Hi all, After replying to r-help earlier today on the merge() related thread, I noted a trivial grammatical error in the description for the 'suffixes' argument in it's help file. A patch against the current SVN trunk version of merge.Rd in ..library/base/man is attached and pasted here: --- merge1.Rd 2016-06-08 13:34:35.000000000 -0500 +++ merge2.Rd 2016-06-08 14:03:34.000000000

Hi All, I have tried every fix on my try or tryCatch that I have found on the internet, but so far have not been able to get my R code to continue with the "for loop" after the lmer model results in an error. Here is two attemps of my code, the input is a 3D array file, but really any function would do.... metatrialstry<-function(mydata){ a<-matrix(data=NA, nrow=dim(mydata)[3],

Hi folks, I am tearing my hair out on this one. I am using an example from Pinheiro and Bates. ### this works data(Orange) mod.lis <- nlsList(circumference ~ SSlogis(age, Asymp, xmid, scal), data=Orange ) ### This works mod <- nlme(circumference ~ SSlogis(age, Asymp, xmid, scal), data=Orange, fixed = Asymp + xmid + scal ~ 1, start =

I'm resending this message because I did not include a subject line in my first posting. Apologies for the inconvenience! Tanja > Hello, > > I'm trying to fit a generalized linear mixed model to estimate diabetes prevalence at US county level. To do this I'm using the glmer() function in package lme4. I can fit relatively simple models (i.e. few covariates) but when

I am making the question clear. Please help. > Dear R experts > > I was using kinship package to fit mixed model with kinship matrix. > The package looks like lme4, but I could find a way to extract p-value > out of it. I need to extract is as I need to analyse large number of > variables (> 10000). > > Please help me: > > require(kinship) > > #Generating

Hi, I am doing a binomial GLMM with a random intercept using the formula below, but I always get the same warning message. > m01 <- lmer(pres~ HT + DN + dtree + DNm + cmnhi + cmxes + cplan + craan + lfphal0100 + lfov0100 + lfop0100 + (1|plot), family=binomial, data=vphal, verbose=TRUE) 0: 6309.9448: 0.459924 -5.20747 -0.378722 0.558779 -0.200922 -0.0488451 -0.397844 0.367916 -2.09820

I'm testing out a new version of coxme and R CMD check fails with "could not find function ranef" (or random.effects or fixef, or anything from nlme). The NAMESPACE file has the line below importFrom(nlme, ranef, random.effects, fixef, fixed.effects, VarCorr) and nlme is declared in the DESCRIPTION file as an import. I feel that I must be staring at some obvious (but

Dear r-helpers, Spencer Graves and Manual Morales proposed the following methods to simulate p-values in lme4: ************preliminary************ require(lme4) require(MASS) summary(glm(y ~ lbase*trt + lage + V4, family = poisson, data = epil), cor = FALSE) epil2 <- epil[epil$period == 1, ] epil2["period"] <- rep(0, 59); epil2["y"] <- epil2["base"]

Dear R group, Tried to turn off the html in yahoo.  So far  not successful.  Apologies! I tried to get xyplot shrink fit for my mixed model.  But, the mixed model line is not seen in the graph. I would like to know if there is anything wrong with my code. Thanks, A.K. (fm1 <- lmer(Response3 ~1+ Wavelength*Start_Resp*time + (1|resid) + (1+time|Subject_BDat), family=binomial, data=Behavdat,

Dear list, This is more of a stats question than an R question per se. First, I realize there has been a lot of discussion about the problems with estimating P-values from F-ratios for mixed-effects models in lme4. Using mcmcsamp() seems like a great alternative for evaluating the significance of individual coefficients, but not for groups of coefficients as might occur in an experimental design