Questions tagged [glmmtmb]

R package to fit linear and generalized linear mixed models with various extensions, including zero-inflation.

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interpreting output for glmmTMB for zero-inflated count data

I have been trying to read all the documentation I have, but I'm still not sure what the difference is between the "conditional" and zero-inflated models in the output of the glmmTMB. Below is some ...
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20 views

Large standard error of intercept and low overdispersion parameter from negative binomial hurdle model using glmmTMB

I am running hurdle models on some count data using the R package glmmTMB. For one of my models, I tried the "truncated_nbinom1" family, but this model fails to converge. When I use the family "...
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How to apply arguments to multi-model dot and whisker plot of coefficients? [migrated]

I am trying to create a plot like the following (taken from https://cran.r-project.org/web/packages/dotwhisker/vignettes/dotwhisker-vignette.html), but with no intercept, and with no rescaling: I ...
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GLMM: Define zero inflation varying across sites

I am fitting a glmm for count data as follow: ...
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37 views

Model Selection- Poisson and Negative Binomial

I have run 2 GLM models with same variable specifications except that one was run with the response variable following a generalized poisson distribution and the other with a negative binomial ...
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Interpretation of interactions in inverse gamma glmm

i want to calculate the effects that the interaction between zone (4 levels), species (2 levels) and distance from contact zone (continuous) has on the pulse repetition period - song rate of the two ...
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25 views

Emmeans & effects packages: Post-hoc tests for Tweedie glmmTMB model

Are there any problems with using the effects and emmeans packages to interpret glmmTMB models with Tweedie distributions? I have glmmTMB models using the Tweedie distribution, and I want to draw ...
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29 views

I have a proportion DV with true 0 and 1. Which mixed modelling approach (in R) is most recommend?ed?

Hope this isn't too much of a dumb question. I've been searching for a definitive answer, and now I've got choice paralysis. I have a proportional DV (accuracy) with true 0 and 1 values averaged for ...
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1answer
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Confused about over dispersion for my beta distribution

I have percentage data so I am using a beta distribution and I want to do a mixed-effect model so I am still trying to decide between glmmTMD or the brm packages. I saw somewhere that some ...
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76 views

What to do when you have significant autocorrelation in a glmmTMB logistic regression model (easily reproducible code provided)?

I have significant autocorrelation apparent from acf and pacf plots of a binomial GLM. My question is how can I solve this ...
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6 views

Avoiding potential for over estimating rates of small counts in zero-inflated poisson

Fitting glmms I have encountered cases where zero-inflated Poisson models drastically over-estimate rates for response variables with very low counts despite being the better fit. Is there a an ...
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41 views

Mixed effect zero inflated negative binomial model in R: use of Dharma package, glmmTMB and glmmAdaptive

I am having trouble fitting a mixed effect zero inflated negative binomial model to my data using the GLMMadaptive package: negbi_1 <- mixed_model(fixed=MA ~ ST + AG + SU +SO +Y, ...
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29 views

Zero offset values, glmm poisson/negative binomial distribution with

I have a data set that consists of video observations of carpenter bee nests under three treatments: a control, mothers removed and mothers and worker removed. I have counts of twenty behaviours as ...
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11 views

Buld prediction intervals for glmmTMB

I'm using glmmTMB to build a mixed effect logistic model from which I want to draw predictions. The predict() function applied to a glmmTMB model allows extracting the ML prediction and the relative ...
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1answer
42 views

Mispecified random effects in mixed model

This is a simplified example of my model formula: Response ~ Treatment * Condition + (1|Plot/sublot) Treatment and Condition have 2 levels each, (say A/B and a/b)...
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Offsets variable subjects and behaviors

I have a set of behavioural data. It consists of about 600+ 50 mins long observations within 35 different bee nests, with many different numbers of observations per nest, and variable numbers of bees ...
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Issues with Conway Maxwell Poisson Family in glmmTMB

I'm having issues running the the Conway Maxwell Poisson family (compois) in glmmTMB. I have under dispersed data (0.5). I am running a mixed model. 3 predictor variables, 2 random effects, n=1000. ...
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Bootstrapped interpolated values from a model in glmmTMB?

Is there a way to bootstrap interpolated values from a model in glmmTMB? After I have fit a GLMM I like to interpolate known response values into the model using a modified version of Venables' ...
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28 views

Specification of AR1 correlation structure for multilevel zero-inflated Poisson model with sparse outcome

I am trying to specify an AR1 correlation structure for a multilevel zero-inflated Poisson model using glmmTMB. A sample of the ...
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1answer
67 views

Diagnostic plot (residual vs. predicted) of a glmm using DHARMa

I used glmmTMB to fit a model with beta distributed errors, zero inflation, several nested random effects and temporal correlation. I then used the diagnostic plots available in DHARMa. My residual vs ...
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PIT histogram for multilevel model

I realized a poisson multilevel analysis with randon effects, using the package glmmtmb, and now I'd like to check the adjustment with PIT histogram Is there any ...
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1answer
143 views

crossed random effects with autoregression, glmmTMB

I am working on data that have crossed random effects as well as a autoregressive covariance structure. I would like to check if there is something unlogical about my approach, as the model I would ...
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25 views

Plotting slopes and 95% confidence intervals with the effects package

I'm having some trouble getting the effects package to make the graph I want. I'm using the predictorEffects function to generate predictions for the effect of two 2-level factors (species & ...
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60 views

P-value of 1 and parametric bootstrap for random effects in glmmTMB

I am running mixed models in glmmTMB, and I'm using likelihood ratio tests to test the significance of my random effects. Mostly this is working fine, but in some cases the LRT gives me a p-value of 1 ...
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OLRE's vs. Beta Binomial Model for Overdispersed Mixed Effect logistic regression with proportion data?

this is a long post, as I wanted to be sure to provide all relevant information regarding my data, model, the methods that I have tried so far, and my diagnostic plots. If there are ways I should ...
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1answer
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Is setting a certain covariance structure between random effects and zeroing R equivalent to setting this structure exclusively in residual matrix?

I'm wondering whether setting, say, a compound symmetry covariance structure between random effects and setting the residual covariance to 0 is effectively the same as not using the random effects G ...
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112 views

Is this possible to fit a MMRM (SAS REPEATED) with compound symmetry or AR1 model with glmmTMB?

MMRM (Mixed effect Model Repeat Measurement) models are special cases of the mixed models, where no random effects are used, only the residual covariance is modelled. This is commonly used for ...
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106 views

Understanding AR1 through the glmmTMB package

I've been working through a reproducible example to better understand AR1 covariance matrix using the glmmTMB package. I have a couple of questions, even if only ...
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1answer
178 views

Interpreting random effects in zero-inflated models

For context, I have a longitudinal study measuring counts of bacterial sequences in human stool collected during a dietary intervention. Initially, I was going model the change in each bacterium (...
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73 views

Model convergence problem; non-positive-definite Hessian matrix - small variance

I want to see the differences between the 6 conditions regarding a centralization index (CI). I am trying to GLMM using the package glmmTMB in R but the following warning appears Warning messages: 1:...
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330 views

How are PQL, REML, ML, Laplace, Gauss-Hermite related to each other?

While learning about the Generalized Linear Mixed Models, I often see the above terms. Sometimes it seems to me these are separate methods of estimation of (fixed? random? both?) effects, but when I ...
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1answer
161 views

Why does the glmmTMB gives different fixed effects when random slopes are requested vs just intercepts?

I am trying to fit a beta regression to my data using mixed models, as there are 4 repeated observations per subject. Legend: p = (time) point: t1...t4 ID = subject ID When I try: ...
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1answer
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glmmTMB-posthoctest-lsmeans [closed]

all. I've fitted the following model model1<-glmmTMB(total~treatm+(1|factor1)+(1|factor2)+(1|factor3), data=mydata1, family=nbinom1) and I performed a post-...
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How to determine likelihood of each observation from a fitted model in R?

Suppose you have the following data and model: ...
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1answer
243 views

Model converges in glmmTMB but not lme4, why?

I am running what I suppose is the same mixed-effect model with a negative binomial distribution (log link) in both lme4 and the glmmTMB package in R. Code shown below: ...
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24 views

Correlation between two variables from nested, non-normally distributed, semi-continous / count data

I am interested in correlating the physical distribution of cell types and cellular material within tissue that has been imaged as a large grid of images (each grid is a datapoint). My data comprises ...
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1answer
85 views

GLMM for continuous response in $[0, 1]$

I am looking into GLMMs because my linear model residuals' plot has a weird pattern (some residuals form a diagonal pattern), and a lack of normality was also confirmed with a Shapiro test. ...
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1answer
298 views

Help interpreting output from glmmTMB and Ben Bolker's overdispersion function

Just wondering if anyone can help with interpreting the output from Ben Bolker's over-dispersion function (please see link below): https://bbolker.github.io/mixedmodels-misc/glmmFAQ.htmlhttps://...
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113 views

Negative binomial random effects models (glmmTMB/gamm/gamm4)

Can anyone help please. Am I missing something fundamental here? I would like to test for a Cave and a Category effect in the same model, and I'd like to know if I've specified the random effects ...
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46 views

Is It Valid To Calculate Model-Averaged Confidence Intervals In the Same Way As Model Averaged Predictions?

I'm fitting a series of mixed-effects models, and I'm trying to calculate the model-averaged predictions and their confidence intervals. If I have a set of $R$ models $\{M_1,...,M_R\}$ I know that ...
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1answer
39 views

How to calculate individual covariances and residual covariances in a multivariate mixed model

I need enlightenment in calculating individual covariances and residual covariances in a multivariate mixed model. I'm going to use the dataset 'Owls', present in the glmmTMB package to replicate ...
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Interprete GLMM Estimates with log link

i am relatively new to this field and this is my first time using Generalized Linear Mixed-Effects Model. my response variable is Reaction Time (RT) and i have two fixed effects: prime and type. both ...
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Checking a beta regression model via glmmTMB with DHARMa package

I would like some clarification whether my model is well specified or not (since I do not have much experience with Beta regression models). My variable is the percentual of dirth area in the denture....
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39 views

Log transformation vs. log link function: Analysing proportional differences

I'm analysing the effect of rhizobial inoculation, fertilisation, and species identity on plant shoot weight. The two species I'm studying have different mean weights, so I'm mostly interested in ...
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1answer
226 views

Tweedie distribution without zeroes

Recently I've found the Tweedie distribution useful for modelling my plant shoot weight data in glmmTMB. I started using it because my shoot weight datasets have many zeroes, and it has yielded better ...
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204 views

Differences between glmmadaptive Vs lme4 and glmmTMB in ICC measurement

This is my first question, so please be kind... I am currently modelling a GLMM with a binary outcome with many (500+) clusters but cluster size of 2 (by design - there can be no more than 2 per ...
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2answers
422 views

Dealing with Overdispersed Negative Binomial using glmmTMB

I'm new to the world of statistical modeling, but I was wondering if anyone had any input on how to handle overdispersed negative binomial data? I'm working on modeling bat activity as a response ...
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1answer
116 views

How to interprete the p values of cos and sin terms in periodic regression?

I have camera trap data where for each site and hour I have the abundance of wild herbivores. I want to create a model where I can estimate the effect of predator activity on the activity and behavior ...
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Why is the Degrees of Freedom 1 higher when model run with Poisson than Negative Binomial

Because the Negative Binomial distribution would result in there be an extra parameter to estimate the over dispersion, I am confused as to why I am getting a DF of 94 when I run the model with ...
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1answer
233 views

Overdispersion tests from DHARMa and sjstats: conflicting results?

I ran some models for my count data, and did some diagnostics to check for overdispersion. Here is a dharma graph, which as I understand, indicates no overdispersion. And this is the result I get ...