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

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model comparison when alternatives are not all nested within one another

I am running a glmm with three fixed effects: opponent 1 size ("1") opponent 2 size ("2") opponent 1 size - opponent 2 size ("diff") I am unable to run all three variables in the model at once ...
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should I include random effects in a model if they aren't statistically significant?

should I include random effects in a model even if they aren't statistically significant? I have a repeated measures experimental design, in which each individual experiences three different ...
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44 views

How to fit Graded Response Model with lme4::glmer

Thanks to Rijmen et al.(2003), we can fit GRM to the data with lme4::glmer. I think Rasch model is straightforward, with ...
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55 views

Include nesting factor as fixed effect in a GLMM

I have the following GLMM: success ~ age + gender + group/task + (1 + group/task|school/subject), family = binomial I want to know whether participants' ...
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28 views

Fitting GLMMs for binomial data produces Error and Warning messages when using different fitting procedures in R.

I am trying to fit GLMM's to my data using the glmer function available in R's lme4 package. The data is available under the name block1and2 at: ...
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97 views

R lme4 1.1-7: REML=FALSE giving error “extra argument(s) ‘REML’ disregarded ”

I'm trying to fit a model with the function glmer (lmer4 1.1-7 package) in R using REML but I just get an error saying ...
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9 views

References for crossed random effects

Could you recommend some examples of published articles that used general mixed-models or glmer() function with only crossed random effects and no random slopes. Using glmer function, the model will ...
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17 views

Usage of rma.glmm() for random effect single group study

Below are first few rows of my data that need to be analysed. I would need to understand the relation between number of years and survival rate. My statistical teacher advised on using rma.glmm() ...
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32 views

What GLM family and link function for “proportion of time”?

A simple question to which I don't seem to find the answer anywhere. I have a response variable duration of time spent doing A of individuals tested for ...
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230 views

Likelihood and estimates for mixed effects Logistic regression

First let's simulate some data for a logistic regression with fixed and random parts: ...
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36 views

correct use of Negative Binomial with a Geometric distribution in a mixed model (glmmPQL)

I am trying to fit a NB GLMM with a gemoetric distribution. I have come across very little information on this form of regression. And would like some pointers/reasurance. some literature is ...
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23 views

How to specify binomial glmm with random and correlation in R?

I am working on developing a model with a binomial response variable. My data consist of GPS points from tracked animals. The data set is large and contains 15,000 observations from 40 individuals. I ...
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24 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 ...
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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, ...
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33 views

lmmlasso does not work for p>n

I am using the following example from the R manual: ...
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53 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 ...
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49 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. ...
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64 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 ...
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43 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 ...
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20 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 ...
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25 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: ...
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29 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 ...
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1answer
71 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. ...
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38 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 ...
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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 ...
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1answer
56 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 ...
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63 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 ...
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89 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 ...
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25 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. ...
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214 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. ...
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1answer
82 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: ...
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273 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 ...
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37 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 ...
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47 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 ...
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55 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 ...
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45 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 ...
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27 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 ...
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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 ...
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92 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 ...
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84 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 ...
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57 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 ...
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15 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 ...
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69 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 ...
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147 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, ...
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165 views

How to handle underdispersion in GLMM (binomial outcome variable)

I'm working on the following model in R: ...
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60 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 ...
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57 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 ...
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17 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?
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113 views

Binomial GLMM: Model validation & ceiling effect

My data has a binary response acc(correct/incorrect), one continuous predictor score, three categorical predictors (...