Generalized Linear Mixed (effects) Models are typically used for modeling non-independent non-normal data (eg, longitudinal binary data).

learn more… | top users | synonyms

0
votes
1answer
12 views

GLMM for SNA and non-independency data

I contact you because my case is particular and I don’t know much about GLMM. I have data of social networks (network metrics) of a nonhuman primate species. These data are by nature non independent ...
3
votes
1answer
35 views

Taking a random factor into account while measuring a proportion a low N

I need to be neat in measuring the success rate of a treatment. It is anyway pretty high. But as it is all about ecology, multpliying experiments is difficult. I have treated $N = 20$ individuals, ...
1
vote
0answers
27 views

lmmlasso does not work for p>n

I am using the following example from the R manual: ...
1
vote
0answers
13 views

Model diagnostics for a glmmPQL in R mixed-effects model

Several texts (both online and published books) have been reviewed prior to asking this. What diagnostics are accepted as best practise for a generalised linear mixed-effects model fitted in R using ...
0
votes
0answers
15 views

Compare LMM GLMM (generalised linear mixed model, negative binomial) by numerical measure (AIC BIC, cross validation, R² squared) for model validation

How to compare results of generalized linear mixed model (GLMM, negative binomial) with a log transformed linear mixed model (multilevel, hierarchical) . I have a data set (counts), which is nested. ...
0
votes
0answers
26 views

R² (squared) from a generalized linear mixed-effects models (GLMM) using a negative binomial distribution

I try to compute the marginal and conditional R² for a GLMM using a negative binomial distribution by following the procedure recommended by Nakagawa & Schielzeth (2013) . Unfortunately, the ...
0
votes
0answers
17 views

How to use the Huber/White estimator of covariances in a generalized linear mixed model (glmmPQL) in R?

An analysis was implemented in SPSS 22 that uses the "Generalized Linear Mixed Models" feature of the program. Now I am looking for a way to port this to R. I use the glmmPQL() function of the MASS ...
0
votes
0answers
16 views

Specifying a glmm for panel data

I'm trying to predict counts based on variables sampled on a monthly basis as well as a few that are not related to time. In several places I've read that the MCMCglmm package in R would be ...
0
votes
0answers
24 views

differences between different notations in mixed effects model

I have never been so confused in my life. Could anyone please tell me what is the difference between the following mixed effects models: ...
1
vote
0answers
22 views

glm or glmm model with unequal variance

I am applying a GLM model with binomial family: glm(response ~ Treatment, family = binomial, data=dat) The only explaratory variable treatment is a categorical ...
0
votes
1answer
59 views

Linear mixed effect models with two independent variables

I am estimating a random intercept and a random slope model using the following R code. My dependent and independent variable are both continuous. ...
1
vote
0answers
34 views

R-squared for linear mixed effects model [duplicate]

I ran linear mixed effects model in R. model<-lmer(yld ~ rain + (1+rain|state),data=data,REML=FALSE) Is there any way I can generate an R-squared for the ...
3
votes
0answers
35 views

Elastic net package for mixed effects models?

I know about glmmLasso but would prefer to use elastic net. I wonder if there are any glmm analogues of glmnet out there, or if ...
1
vote
1answer
33 views

Measuring goodness of fit for mixed logistic regression model - inconsistent results from R squared and AUC

I am trying to assess the goodness-of-fit or accuracy of 6 generalised linear models. I first assessed this using AUC (calculated from function auc1 described here), and got results ranging from 0.65 ...
1
vote
0answers
48 views

Is this longitudinal data too complicated for GLMM or GEE?

After writing this post, I've realized that I am running around in circles, chasing my tail. Any help approaching this problem would be greatly appreciated, as I think I just need to bounce ideas ...
0
votes
1answer
54 views

Testing significance of a random effect glmmADMB model

Below is the output from a model of novel object test scores fit with the nbinom1 (quasi-Poisson) option in glmmADMB. I used ...
0
votes
0answers
23 views

How to account for multiple & varying amounts of observations per factor level & still retain info? As a random effect in GLMM or take the mean?

I would appreciate any help! Specifically I would like to know which option is best. Question Does Var2 influence Var1 in relation to the factor(Ind), and does Var3 & Var4 also have some effect. ...
0
votes
0answers
110 views

Q: plot glmm fixed and random effects (glmer in package lme4) using ggplot2

I am trying to visualize the results from a glmm that I ran with the lme4 package. ...
0
votes
1answer
57 views

Significance of the overall model GLMM using lme4

Maybe it's a basic question, but I'm learning about GLMM using the lme4 package. I'm confused about the way that I can know the significance the overall model using glmer. First, the random model is: ...
1
vote
1answer
159 views

Coefficients from glmer in R

In a mixed effect model where the intercept is random effect and the slope is fixed effect (see the code below), I understand the output of summary(glmer(...)). But ...
1
vote
0answers
30 views

Should I use a beta-binomial or binomial glmm?

I have several data sets on wildlife disease incidence. One of the issues with my dependent variable is that it represents only current infection status, therefore 0 (no disease) can represent either ...
0
votes
0answers
31 views

Calculating random effects from a glmerMod object (r package lme4)

Using the lme4 package, how does ranef() calculate (or extract) estimates of random effects from a ...
0
votes
0answers
54 views

GLMM and two slopes

My outcome variable is binomial, and I have 11 independent variables and a time variable. The time variable has different slopes, so I fixed it to time-before and ...
0
votes
0answers
39 views

Quantifying variable importance for GLMM using hierarchical partitioning (in R)

I am interested in quantifying variable importance for a binomial logistic mixed-model regression. My model has 5 fixed effects, and 3 random effects (2 nested). I am doing model selection and ...
0
votes
0answers
21 views

How to compare pairs of coefficients within a glmm with binomial error

I have a generalised linear mixed model with 34 explanatory variables (over 130,000 observations for each). 10 of these variables are different unprotected habitat types, and another 10 are the same ...
0
votes
1answer
18 views

How to compare the magnitude of a response among two groups?

I performed generalized linear mixed models to test the effects of a treatment on two different groups (I performed a model for each group). Now I would like to test which of the groups is most ...
2
votes
1answer
69 views

Interactions between random effects

I'm considering a mixed-effects model to try to understand factors that influence the number of ticks sampled on wild rodents. My data is nested so that I have one tick count per rodent, multiple ...
1
vote
0answers
67 views

Lme4 Error Help: “maxstephalfit…pwrssUpdate”

I am using a mixed model to assess the effects of various treatments on bee behavior (e.g., avoidance frequency - total avoidances per total visits; feeding frequency, and mating frequency). Bee ...
2
votes
1answer
65 views
0
votes
0answers
52 views

Should I be using a GLMM?

I'm looking at the influence of pollen type on whether a flower sets fruit (i.e., yes or no = 1 or 0). Then looking at number of seeds per fruit (1-6 possible). I was told I should use lmer, however ...
1
vote
0answers
13 views

Methods for analysing effects of percentage mortality on population data with zero/low abundances

I want to analyse the effects of percentage mortality from two sources (a predator and a disease) on the population abundance of a host measured at 12 sites for 8 years, with the main aim being to ...
1
vote
1answer
54 views

code needed for p values in GLMM

I need to get p values for the fixed effects in the following GLMM's I ran. Does anyone know of code that I can run that will give me the p values I need? At the moment the output from the ANOVA only ...
1
vote
0answers
98 views

Reading the output from a GLMM run in R

I am a complete novice and dummy when it comes to statistics so I apologise in advance... I have been asked to report the results of my GLMMs (I ran two) in a table. This table must state: effect, ...
1
vote
0answers
108 views

How to handle underdispersion in GLMM (binomial outcome variable)

I'm working on the following model in R: ...
0
votes
0answers
53 views

plot effects on glmer

I done a GLMM with the function glmer form lme4, the variable paternity is binomial (yes or no)(model<-glmer(paternity~factor1, factor 2 ....,family=binomial). My model run correctly, but after I ...
0
votes
0answers
46 views

Including a nested factor as random effect in a GLMM

Good afternoon, I'd like to ask for advice on including a nested factor as a random effect in a GLMM. I've read other threads in this forum, but still am not able to answer my question. Any help is ...
0
votes
0answers
16 views

Does GLMM or LMM already give us planned contrasts?

I use GLMM and LMM to find significant factors for my data. And could I ask if the results from these two models already give me planned contrasts? Or do I need to run them separately?
1
vote
1answer
88 views

Binomial GLMM: Model validation & ceiling effect

My data has a binary response acc(correct/incorrect), one continuous predictor score, three categorical predictors (...
0
votes
1answer
34 views

GLMM: Many models?

I use R to run GLMM models in my study. Then in my situation, I have 10 independent variables and one of them has 3 categories. Then, when I run the GLMM, it usually uses one category as baseline, so ...
1
vote
0answers
34 views

Prediction Model for the number of defects

I work at a software company, and we are trying to build a statistical model to predict the defect density (the number of defects that exist in a certain software release that is delivered to a ...
1
vote
1answer
281 views

Binomial GLMM with categorical predictors: p-values?

My data has a binary response (correct/incorrect), one continuous predictor score, three categorical predictors (race, ...
1
vote
0answers
92 views

Binomial mixed model with categorical predictors: model selection and getting p-values [closed]

My data has a binary response (correct/incorrect), one continuous predictor (with NaNs) and several categorical predictors. I want to add a random intercept for a ...
1
vote
0answers
73 views

Logistic regression with binary inputs

Is logistic regression an appropriate classifier when the input data are binary? Say we are conducting an experiment where the subject is presented with blue and green circles of varying shades, and ...
1
vote
0answers
34 views

How to assess whether IQ predicts emotional experiment more at time 1 or time 2 controlling for covariates?

I have the following data set of a two-wave longitudinal study in educational psychology. A group of 400 people did some questionnaire on IQ, personality and two different emotional states (sadness ...
0
votes
1answer
36 views

Generalized linear mixed model: what is base dependent variable?

I have run Generalized linear mixed model with glmer in lme4. I use R version 3.0.1. My dependent variable is binary (correct or wrong). And this is my results: ...
5
votes
0answers
254 views

Meaning of a convergence warning in glmer

I am using the glmer function from the lme4 package in R, and I'm using the bobyqa optimizer ...
1
vote
0answers
48 views

Calculating point estimates from model-averaged parameters

I'm using an IT-approach and multi-model inference with some count data. I have used model averaging to obtain parameter estimates from several GLMMs with Poisson-lognormal errors (Poisson family ...
4
votes
2answers
180 views

extremely left-skewed response variable - how do I model this dataset?

This is a histogram showing my response variable. The response is # (or proportion? or percent?) of aphids eaten off of cards in fields, to model predation by natural enemies. Predictors: fixed ...
0
votes
0answers
68 views

How to interpret the results from random coefficient Poisson data analysis

I have fitted random coefficient Poisson analysis in R. I have obtained the following results: Generalized linear mixed model fit by maximum likelihood ['glmerMod'] Family: poisson ( log ) Formula: ...
0
votes
0answers
44 views

repeated measure ANOVA or GLMM?

I would like to ask for some advice on an analysis that I am doing at the moment. The experiment: I ran an experiment with animals in which I subjected 15 pairs of individuals (one male and one ...