Questions tagged [glmm]

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

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Reporting results of a GLMM with Helmert contrast in fixed effects

I would like help deciding how to report my results. I am looking at whether different demonstrations affect performance in a forced-choice binary task. Demonstrations were done either by a puppet or ...
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67 views

Don't understand why glmm random effect variance is zero. Have reviewed similar questions still dont get it

I study a colonially-nesting bird species. I am trying to perform an AICc evaluation of GLMMs for a nest site selection study. I collected data at nest sites and paired random sites. I want to ...
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24 views

Why are the confidence intervals so large for the difference of differences?

I have run a generalized linear mixed effects model with the glmmTMB package to determine if there is an interaction between two categorical predictors, treatment and location, in predicting the ...
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Can you use nAGQ = 0 with the Poisson distribution?

I am working with a GLM with lots of random variables and Poisson distribution. I get the error 'boundary (singular) fit: see ?isSingular' and so looked up ways around this. I found someone ...
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1answer
98 views

Model is nearly unidentifiable: very large eigenvalue

I'm fitting a generalized linear mixed model using glmer() and I'm getting a warning that I don't understand: ...
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16 views

random factos really significant?

I have some confusion about random factors inclusion or not. I've used the function glmer.nb of the library MASS to analyse the effects of two fixed factors (temperature: 2 levels and salinity:3 ...
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15 views

Conflicting residual diagnostics for GLMM for binary data: zero-inflation

I fitted a mixed logit model with crossed random effects in lme4_1.1-21::glmer to some experimental binary data. The maximal random-effect structure justified by ...
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24 views

Diagnostic plot of glmm model

I am very new to R and I have a problem with the diagnostics of my models...can anyone help me please? i have run my model: Modell_ia8<- glmer(vote~edu1 + age1+ female+eink1+scltrst+poltrst+...
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1answer
38 views

Generalized linear mixed models, extracting effects at all time points using summary, for each group./ [closed]

A bit of lenghty title, but summarizes my problem well enough. Currently I am part of longitudinal-data classes and one of my tasks consists of extract the treatment effects of all the time points for ...
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1answer
37 views

Hierachical Random Mixed effect sizes

When using a mixed effect model the rule of thumb seems to be that you need at least 5 levels to use a random factor . Is this still True when you have a hieachical model. i.e A - 4 level factor B - ...
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28 views

AICc for small sample size

I would like to test the effects of salinity and temperature on parasite infection. Temperature and salinity are the fixed factors, the first one has two levels, the second one three levels. ...
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1answer
22 views

glmm (poisson or negative binomial) which explain the significance of each single level [closed]

I'm using the function glmer.nb of the library MASS to analyse the effects of two fixed factors (temperature: 2 levels and salinity:3 levels) and nested random factor (Individual ID/room) on parasite ...
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2answers
53 views

Appropriate model choice for analyzing a cluster based longitudinal randomized controlled trial

I am performing a randomized controlled trial (RCT) of an educational intervention to improve knowledge, belief and practice among healthcare workers in hospitals. One hospital is assigned to the ...
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24 views

Enforcing positive sign on random effects coefficient

I have a mixed effects model in brms of the form (lme4 notation): y ~ x + (1 + z1 + z2|g) where g is a grouping factor on ...
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1answer
37 views

Model validation in R - Gamma GLMM

I'm trying to model a response variable y with respect to a nested variable x in R. First of all, I fitted a linear mixed model (LMM) as it follows: ...
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17 views

How to choose the independent variables in a GLMM without performing stepwise selection? With a global model? How to decide then?

I am trying to conduct an inferential binomial GLMM with a large dataset and many independent variables. I was attempting to do a stepwise AIC selection but keep reading it is a bad idea. However, ...
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18 views

confused about effects vs. means parameterization in R - which is right for Anova?

I'm running a few GLMs and using the effects (e.g. glm(var1~var2...) ) and then means parameterization (i.e. glm(var1~-1+var2...) -- the one without the intercept). I understand that effects gives you ...
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1answer
42 views

glmm models - predictions and results presentation

I'm working with GLMM and a binomial distribution to find the best model for my biological data. I'm currently writing my PhD and I have some trouble to present my results. I read and learn a lot ...
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47 views

Error: matrix-valued responses are not allowed in glmmTMB

I have some problems fitting a glmmTMB on my data. I am conducting a large synthesis analysis in an agricultural context including distance within the field and adjacent habitats. The model structure ...
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1answer
28 views

Predicting new subject observations in repeated measures data

Dataset Say I have a repeated measures dataset given as follows. There are 10 subjects, and each subject responded 100 times. ...
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23 views

How to interpret the results of GLMM? [duplicate]

I have run a GLMM model using function glmer of package lme4. But I do not know how to interpret the results. The summary of the model is: ...
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1answer
53 views

Linear Mixed Effects Models for Truncated Normal Distribution

I would like to analyze amplitude differences of discrete oscillations that were detected in a time-series using a thresholding method between three different conditions. The number of discrete events ...
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72 views

R: lme4 vs. glmmTMB for binomial GLMM

I am fitting a GLMM to test if parasite prevalence in snails (positive snails divided by total snails) differs between different sites (site_type). Sites were ...
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18 views

How to formulate a generalized linear mixed model?

I have a data set like this: population: numeric country: categorical city: categorical, nested in country century: categorical, crossed by city and country year: categorical, nested in century, ...
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How many folds should I use in cross-validation and is it a bad idea to restrict it?

Background I am working with data that looks like this: ...
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How to properly integrate data from multiple studies in a training/testing classification framework?

I currently have data from several studies, with each having different sample sizes and possibly different set-ups. There is a common binary variable of interest across all studies that I would like ...
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1answer
22 views

What if the dispersion parameter of a glmm model is not around 1?

I am using the glmer function in package "lme4". The results shows that: AIC BIC logLik deviance df.resid 96.7 105.5 -44.4 88.7 62 So the dispersion parameter is ...
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1answer
26 views

Why do I get so different estimations with glm and glmer?

I am using the glmer function (lme4 package) to get estimations in a Poisson regression model (generalized linear model). I ...
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1answer
46 views

An R package for GLMM estimation with two random effects?

I am looking for an R package to make an estimate on a general linear model with two random effects. I was used to lme4 (function...
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1answer
50 views

GEE vs GLMM in large sample size?

I am running two longitudinal models for two different populations I'd like to compare. N1=4,000 individuals (translated into about 20,000 rows; 18 variables) and N2=400,000 individuals (~4 million ...
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1answer
38 views

Finding GLMMs that fit my count data for multiple datasets

I need some help finding a model that fits my data. I'm using GLMM's to test the effect of nitrogen level (numerical), species (two-level factor), and the interaction between these two variables, on ...
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1answer
26 views

Repeated measures regression using GLMM if there are varying numbers of measurements per subject

Aim: To develop a predictive model for an infection, judged condition negative/positive by an assumed gold-standard. Data: Longitudinal data for a number of subjects, at each time point comprising a ...
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2answers
72 views

GLMMs for count data with glmmTMB: random slopes specification, cross-level-interaction and strange results

folks, I recently found the great glmmTMB package which I hoped would help me with my models. My data are 60,000 facebook posts that are nested in 51 companies (i.e., the posts by these companies). ...
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1answer
87 views

General linear mixed model in R which will fit quasi family [closed]

I am trying to run a GLMM with a quasibinomial family (my data is 0 inflated and I have a negative min x value), but am receiving this error message as quasi families cannot be used in glmer: ...
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60 views

GLMM in R doesn't converge, nearly unidentifiable [duplicate]

I'm building my GLMM using r. ...
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2answers
156 views

R: How to fit a GLMM in nlme

I want to compare lme4 and nlme packages for my data. But I'm confused by how to use syntax in nlme. I'm working with Mixed-Effects Models in S and S-Plus (Pinheiro, Bates 2000) and the current ...
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random effect variance as pseudo-rsquared in GLMM

Suppose I have data on the abundance of a species across multiple sites that differ in some covariate of interest. Suppose that the logarithm of the abundance (logAbun) meets assumptions for linear ...
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1answer
41 views

Using variance-covariance matrix of mixed-effects logistic regression to obtain p-values for custom contrasts

My question is a follow-up to this question, following through on @Isabelle Ghement's excellent series of responses. I just want to run this past some people in the know to see if what I am doing is ...
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R glmmadmb continuous vs categorical interaction multiple comparisons

I'm running a model using glmmadmb and I'm not sure how to do multiple comparisons on an interaction between categorical and continuous predictors. Here are details on the model and data: My ...
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1answer
101 views

Computation and interpretation of marginal effects in a GLMM

I am currently working on a GLMM model which uses a Poisson distribution and need to compute and interpret marginal effects from this model. The model outcome consists of a count (COUNT) collected ...
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52 views

incorporating temporal autocorrelation into GLMM

I am examining the relationship between presence at a site over time, and I am interested in determining if there is a decline in presence as an individual gets closer to their final departure. Due ...
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1answer
27 views

How to interpret effects of predictors with large confidence intervals in GLMM?

(This question is somehow related to my previous one) My aim is to find out about which effect several predictors have on my response variable, I am interested in the direction and magnitude of the ...
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20 views

Distribution/analysis method for small dataset with many small/zero values

I have a relatively small dataset (160 observations), of which a very large number of values for response variables are zero or very small (e.g., 114/160 values are 0; range 0-4250, with only 11 ...
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1answer
127 views

Which random effects to include in this GLMM?

In my study growth of plants was measured in different years on different plots (all plants were measured in all years). The question I'd like to answer with my model is: Which factors influence ...
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130 views

Covariance structures in glmmTMB for temporal autocorrelation

I'm running a zero-inflated, mixed-effects negative binomial model with the glmmTMB package in R. My current format: ...
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1answer
19 views

Differences between sexes across months with repeated IDs

I'm trying to figure out the best way to analyze the difference between sexes and across months for the means of a specific behavior (most individuals measured have repeated measures across the 5 ...
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1answer
65 views

Interpretation of fixed effect coefficients from GLMs and GLMMs

I am currently interpreting some glm's and glmm's based on distributions with log link functions (gaussian - log, and negative binomial) and have started going in a bit of a loop regarding the ...
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1answer
392 views

Linear mixed effects model with time series

I have been reading through the different posts here on linear mixed effects models, but am still very unsure whether I have understood the task correctly, therefor I am reaching out for help by the ...
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Underperforming participants (<50% accuracy) in LMM

I have to perform a linear mixed model analysis on behavioural conflict paradigm data (ie analysis of congruency effects) and I'm struggling to find reliable sources on what to do with respect to ...