similar to: MCMCglmm multinomial model results

> On Mar 22, 2018, at 1:31 PM, Michelle Kline <michelle.ann.kline at gmail.com> wrote: > > Hi, > > Thanks in advance for any help on this question. I'm running multinomial > models using the MCMCglmm package. The models have 5 outcome variables > (each with count data), and an additional two random effects built into the > models. The issue is that when I use

Hi David, Thanks for your comment. I haven't posted the data because they are unpublished and include human subjects so there are issues with sharing on a list serv, but I thought perhaps someone had encountered a similar problem and would already know the answer. I will reconsider whether my University's ethics approval would allow me to post the data and update the question if I think

Hi all, I previously emailed about a multinomial model, and after seeking some additional help, realized that since my response/outcome variables are not mutually exclusive, I need to use a multi-response model that is *not* multinomial. I'm now trying to figure out how to specify the priors on the multi-response model. Any help would be much appreciated. My data look like this: X

Hi, I am sorry if this is perceived as a C++ question rather than an R question. After uploading an R library to CRAN (MCMCglmm) the C++ code failed to pass the memory checks. The errors come in pairs like: Mismatched free() / delete / delete [] at 0x4A077E6: free (vg_replace_malloc.c:446) by 0x144FA28E: MCMCglmm (MCMCglmm.cc:2184) Address 0x129850c0 is 0 bytes inside a block of size 4

1. (Mainly) Statistical issues are generally off topic on this list. You might want to try the r-sig-mixed-models list instead. 2. However, I think a better answer is to seek local statistical expertise in order to have an extended discussion about your research intent in order to avoid producing yet more irreproducible psychological research. Cheers, Bert Bert Gunter "The trouble with

Hi, I ran R (version 2.9.0) CMD build under root in Fedora (9). When it tried to remove "junk files" it removed EVERYTHING in my local account! (See below). Can anyone tell me what happened, and even more importantly if I can I restore what was lost. Panickingly, Jarrod [jarrod at localhost AManal]$ R CMD build MCMCglmm_2.05 * checking for file

Hi, I ran R (version 2.9.0) CMD build under root in Fedora (9). When it tried to remove "junk files" it removed EVERYTHING in my local account! (See below). Can anyone tell me what happened, and even more importantly if I can I restore what was lost. Panickingly, Jarrod [jarrod at localhost AManal]$ R CMD build MCMCglmm_2.05 * checking for file

Hi, I would like to do a meta-analysis, i.e., a mixed-effects regression, but I don't seem to get what I want using both the nlme or metafor packages. My question: is there indeed no way to do it? And if so, is there another package I could use? Here are the details: In my meta-analysis I'm comparing different studies that report a measure at time zero and after a certain followup

Hi, I ran R (version 2.9.0) CMD build under root in Fedora (9). When it tried to remove "junk files" it removed EVERYTHING in my local account! (See below). Can anyone tell me what happened, and even more importantly if I can I restore what was lost. Panickingly, Jarrod [jarrod at localhost AManal]$ R CMD build MCMCglmm_2.05 * checking for file 'MCMCglmm_2.05/DESCRIPTION'

Hi All, Users have contacted me because they can not build MCMCglmm from source. All are using R 3.3.0 on various machines with different compilers gcc (Ubuntu 5.4.0-6ubuntu1~16.04.2) 5.4.0 g++ (Ubuntu 4.8.4-2ubuntu1~14.04.3) 4.8.4 Mac OS X El Capitan (version/compiler unspecified) The issue seems to be with mixing C/C++ with the repeated error: /usr/include/c++/5/bits/cpp_type_traits.h:118:3:

Hi Bert, That was distinctly unhelpful, and your outward hostility to a field you obviously don't understand reveals a regrettable level of ignorance. By the way, my research is Anthropology despite my job title. Michelle On Tue, May 1, 2018 at 2:48 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > 1. (Mainly) Statistical issues are generally off topic on this list. > You

Dear all, I would like to add mixed effects in a multinomial model and I am trying to use MCMCglmm for that. The main problem I face: my data set consits of a trapping data set, where the observation at eah trap (1 or 0 for each species) have been aggregated per traplines. Therefore we have a proportion of presence/absence for each species per trapline. ex: ID_line mesh habitat Apsy Mygl

Hi All, The data set that I have is a cluster data, and I want to run a HLM mixed model with multi-level response. Here is my data set: response: - Level (num: 1, 2, 3, 4, 5 - 5 levels) Covariates: - Type (Factor: A, B, C - 3 levels) - yr (num: 2006, 2007, ...) - Male (num: 0=not Male, 1=Male - 2 levels) - Ethnicity (Factor: A, B, H, ..., - 7 levels) - ELL (num: 0, 1, - 2

This looks like the result of including a C++ system header inside an extern "C" block. There is no evidence of this happening in the current version 2.22.1. However, it did happen in the previous version 2.22 via the chain of inclusions: MCMCglmmcc.h -> cs.h -> R.h -> various C++ system headers See Writing R Extensions P 108. I would check that the people reporting this bug

Hi R-users: Can anyone give an example of giving starting values for MCMCglmm? I can't find any anywhere. I have 1 random effect (physicians, and there are 50 of them) and family="ordinal"? How can I specify starting values for my fixed effects? It doesn't seem to have the option to do so. Thanks, Ping

Hi to all the people, I'm working with abundance data of some species, but containing too zero values, and the factors are the ones typical in a BACI experiment (Before-and-After-Control-Impact). Thus, these are two fixed factors. As the data does not holds the normality and homogeneity of variances assumptions of clasiccal ANOVA, I'm trying to fit a zero-altered model using the MCMC glmm

Hi, I'm trying to build a mixed-effects model in which I'd like to include either a distance matrix or a phylogenetic tree as a random effect. The troubles I've had are that: 1. Function lmer() in package lme4 only accepts a data frame column as a random factor and not a distance matrix. 2. Function MCMCglmm() in package MCMCglmm only accepts a rooted and ultrametric phylogenetic

On 02/05/18 09:53, Michelle Kline wrote: > Hi Bert, > > That was distinctly unhelpful Not if you actually follow Bert's advice. > and your outward hostility to a field you > obviously don't understand reveals a regrettable level of ignorance. I didn't see any hostility to any field. Bert, like many of us, objects to people blithely and arrogantly applying possibly

Dear R-users, I would like to fit a glmm with cross-classified random effects with the function MCMCglmm. Something along the lines: model1<-MCMCglmm(response~pred1, random=~re1+re2, data=data) where re1 and re2 should be crossed random effects. I was wondering whether you could tell me specifying cross-classified random effects in MCMCglmm requires a particular syntax? Are there any

Dear R-Helpers, I am having troubles with installing with MCMCglmm package and I get the following error with a package "Matrix" Warning in library(pkg, character.only = TRUE, logical.return = TRUE, lib.loc = lib.loc) : there is no package called 'Matrix' Error: package 'Matrix' could not be loaded Execution halted ERROR: lazy loading failed for package