Tagged Questions

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

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Some doubts about using time random effect

I'm starting with lme4 and GLMM. Maybe this question can be basic for experimented researchers, but I'm still learning. I have a pooled data where every ...
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Select the cases from a data.frame that have been used in a GLMM [migrated]

I am trying to see differences in the feeding-rate of one bird species between big forest patches and small ones. I have several forest patches of both sizes, and three years of study. Some ...
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24 views

Convergence warnings in glmer

I am running a Generalized Linear Mixed Model in R 3.0.2 using lme4 1.1-7 for a dichotomous outcome variable (success, 0 = no, 1 = yes) ...
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Data analysis : replication, pseudoreplication and mixed models

I have several questions concerning analysis of data, especially when there are replications and/or pseudoreplications. First, I read an example in « pseudoreplication is a pseudoproblem » where we ...
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Assumptions of Linear Mixed Model

I had data with repeated measurement and nested design. Conventional ANOVA requires strict control on homogeneity of variance and repeated measurement ANOVA requires assumption of sphericity. ...
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15 views

How to measure classification accuracy based on presence only data?

I have a binomial GLMM which I calibrated with data on recreational visits (presence) compared with random controls where no visits were recorded (absence). I generated the controls myself, whereas ...
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1answer
28 views

Assessing the fit of GLMM implimentation of a Rasch model to binary data using lme4

I'd like to assess the fit of the kinds of models described by de Boeck et al (2011) (http://www.jstatsoft.org/v39/i12). They are GLMM implementation of Rasch family models, e.g.: ...
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1answer
32 views

Using interaction terms in an MCMCglmm

I am using MCMCglmm models in R, with hierarchically nested data. The basic structure of the data is as follows - each dyad is a unique combination of focal/other: ...
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17 views

MCMCglmm interpretation of effective sample size

I'm running a selection of MCMCglmm models in R, and have a basic question about the outputs. Based on what I've been reading, one indication that the model is mixing well is a large effective ...
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21 views

Testing GLMM residuals against specific families and link functions (R)

When running a GLMM in R with family=gaussian and link=identity, it's easy enough to test whether normality and homoscedasticity ...
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1answer
74 views

GLMM overfitting solutions

in GLMM faq page http://glmm.wikidot.com/faq there is a statement about overfitting: "One alternative (suggested by Robert LaBudde) is to "fit the model with the random factor as a fixed effect, get ...
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1answer
64 views

Testing whether random effects are normally distributed in R

I've been working on a GLMM in R and I see that an assumption of the test is that the random factor must be normally distributed (that is, unless you're using a package like ...
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1answer
42 views

Can someone look at my method for fitting a GEE to my data?

I’ve been doing some statistical analyses in R on some data. It’s for use in a manuscript I’m hoping to get published in a biological journal. Unfortunately, the tests I ended up having to run are ...
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1answer
24 views

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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68 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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1answer
90 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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146 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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1answer
159 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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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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23 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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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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1answer
259 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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1answer
50 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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28 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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2answers
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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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1answer
38 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, ...
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39 views

lmmlasso does not work for p>n

I am using the following example from the R manual: ...
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112 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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95 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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106 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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84 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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23 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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36 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
95 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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58 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 ...
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1answer
87 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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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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1answer
169 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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388 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
104 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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1answer
403 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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38 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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63 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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62 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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0answers
51 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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35 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 ...