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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1answer
766 views

SPSS: GLMM and(adjusted) odds ratio

I am performing a retrospective study and the relative statistic analysis. I am studying the the risk factors for the occurrence of complications during medical procedures. I have 50 subjects ...
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Calculating effect size for glmm with repeated measures, what is the sample size?

I am new to effect sizes and trying to calculate it for a repeated measure GLMM that looks like this: variable ~ treatment * sampling occasion * year + (1|subject) The variable is continuous, the ...
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35 views

Generalized mixed-effect regression model (GLMM) with negative reaction times as a result of baseline RT subtraction

I am hoping to get some advice for examining differences in reaction times (repeated sampling) as a measure of cognitive load between groups. Dataset: The response variable I am using is reaction ...
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267 views

Interpretation of binomial GLM (glmer) with interaction and results description

I would like to confirm if I am analysing the results of my model correctly and get some advise if I am missing something! I conducted the following model to analyse factors that describe the feeding ...
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1answer
533 views

How does one obtain a type III ANOVA output for a GEE?

ANOVA types I, II and III are explained here. For GLMM and GEE differences see here. I am using the anova() function in geepack to determine the overall impact of several categorical variable in a ...
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28 views

Calculating ICC for a beta-binomial GLMM

I understand that ICC in binomial GLMMs with a logit link can be calculated via R, where the residual deviance is (pi ^ 2) / 3. However, this is assuming that the ...
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2answers
5k views

Effect size in GLMM

In the output of a GLMM, using a binary variable as response variable and continuous variables as explanatory variables [family = binomial(link="logit")], I obtain, for each variable, an estimate ...
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1answer
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How to specify random effects in logisitc mixed effects regression with multiple observations per subject but only 1 outcome per ~50 DV measurements?

I have a dataframe that looks something like this: Each subject got somewhere between 40-120 lesions in a given procedure, and I want to know which dependent variable was associated with "injury&...
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12 views

How to interpret nested GLMM results

I have a dataset like the following: ...
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Residual diagnostics for GLMM using Gamma distribution with identity link

I am using a two-level generalized linear mixed model (GLMM) with Gamma distribution and identity link. In terms of residual diagnostics, I understand that the following assumptions needs to be ...
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1answer
238 views

comparing fixed effects of a binomial GLMM

I got stuck interpreting the result of a generalised linear mixed model (GLMM). Feedbacks on how to compare two coefficients within a categorical fixed effect would be really helpful! To be specific, ...
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1answer
2k views

Residual pattern for mixed models (tried lmer and glmer)

I have studied the effect of site, specific area and depth on amount of organisms on kelp blades. Each site had two different depth with three frames on each depth. From each site I have analysed a ...
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12 views

How to extract the formula of a generalised linear mixed model?

I am trying to extract the formula for a generalised linear mixed model (GLMM). I have made the model from this dataset: ...
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0answers
78 views

Gamma GLMM Dispersion, Random Effects, and CoV (lme4)

So I know that in glm(), with the Gamma family, one can get the dispersion parameter through the MASS package with gamma.dispersion() or can even look at the summary output as a quick estimate. How ...
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2answers
1k views

Problems when adding a variance structure into a GLMM

I did a GLMM model with proportional data using the lme4 package. This model has three categorical independent variables: Age (2 levels) Sex (2 levels) Status (2 levels) "Year" is the random factor. ...
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1answer
213 views

Priors and nested random effects in MCMCglmm?

I am trying to construct a zero inflation Poisson GLMM using MCMCglmm(). I am new to Bayesian Statistics and this function and I am struggling to understand a couple of things. For my data I am ...
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13 views

Testing if groups are statistically different from 0.5 in a binomial GLMM

I have a dataset where I have a binomial (bernoulli - either 1 or 0) response variable, a single fixed factor containing 3 different groups (group1,group2,group3) and a random factor specifying ...
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78 views

Books / Guides / Courses for mixed model? [duplicate]

I have started working for a pharmaceutical firm as a junior statistician recently . In the daily basis I work with lots of studies where I have to apply the mixed models in order to demonstrate the ...
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26 views

How to deal with post-stratification weights in regression settings?

I'm given a longitudinal (i.e., panel/repeated measures) dataset with 2 periods and individuals serving as clusters. The response variable is whether a person would support a healthcare bill, so it is ...
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1answer
93 views

GLM modeling binomial proportions with varying trials and probabilities

A collection of coin manufacturers, $m$, each produces a line of coins, the number of which varies by manufacturer (some produce 3 types of coins, others make 7, and so on). Each manufacturer imparts ...
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1answer
30 views

How can I use relaimpo with glm?

I want to examine the relative importance of the predictors in my model. I know the {relaimpo} package in R allows for the examination of relative importance for <...
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7 views

wildly different parameter estimates in Generalized Linear Mixed Model in response to conceptually irrelevant (?) change

I’m analyzing some data per GLMM with a probit link function and I'm getting some weird inconsistencies between two GLMM specifications that, in my understanding, shouldn't be all that different. Let ...
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1answer
43 views

Grouping Factor throws model off

One grouping factor of my model appears to pose a problem for model fit. Let me elaborate: I tried to fit a GLMM to ecological data for a behavioural study on termites. I did 80 experiments split ...
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1answer
178 views

Problem with repeated measures GLMM in SPSS for psycholinguistic study : Failure to converge and SPSS runs forever

I'm trying to run a generalized linear mixed model in SPSS, with a continuous response variable (ResponseTime), SubjectID as a random factor, Items as a repeated measure, and five fixed factors: three ...
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2answers
177 views

Model misfit with DHARMa - What needs/can be done?

Background I am working with a large dataset that contains longitudinal data on gambling behavior of 184,113 participants. The data is based on complete tracking of electronic gambling behavior within ...
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2answers
799 views

DHARMa diagnostics show significant deviations in KS tests for a glmm with beta distribution

I'm trying to use glmmTMB to fit a beta-distributed generalized mixed effects model with nested random effects. DHARMa residual diagnostics show a KS test with significant deviation. Is this serious ...
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25 views

How can I address the autocorrelation in my glmm?

I am looking at effect of diet on breeding success of birds. For 8 years, I have breeding success (number of chicks fledged / number of eggs laid), as well as Frequency of Occurrence (FO) of Fish in ...
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1answer
16 views

Can I use Gls() or glmer() to predict binary outcomes with restricted cubic splines predictors?

I'm new to rms, as I read the rms book and notes, I saw that the Gls() function could be used to make a longitudinal growth ...
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1answer
218 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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Clarifications on when heteroscedasticity-robust (Huber-White's) standard errors are useful and when they're not

Short version Considering the controversy regarding this practice and having learn that heteroscedasticity should be addressed differently, I wondered: In which cases should one consider computing ...
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1answer
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Is there a way to use weights in glmmLasso in R?

I would like to use weights in a model that I'm fitting with the glmmLasso package, but it looks like there isn't an option for it. I've previously fit models with ...
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1answer
5k views

How do you deal with “nested” variables in a regression model?

Consider a statistical problem where you have a response variable that you want to describe conditional on an explanatory ...
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22 views

GLMM Sample Size Calculation in R

I have an experimental design for a GLMM as follows: independent variable: fixed factor with 3 levels, randomly assigned between groups (condition a, condition b, condition c) dependent variable: ...
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2answers
57k views

How can I test whether a random effect is significant?

I am trying to understand when to use a random effect and when it is unnecessary. Ive been told a rule of thumb is if you have 4 or more groups/individuals which I do (15 individual moose). Some of ...
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24 views

Is a (beta)binomial model fitting for my response variable?

I am working on the evaluation of a speech recognition system we trained. The recognizer basically is given a query utterance containing a single word and should find images containing the appropriate ...
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1answer
28 views

What values are acceptable for the dispersion parameter in GLMM with Poisson distribution on count data?

I'm investigating the effect of three factors (day of observation, parity, gestation) on the number of various behaviors in pigs. For this, I'm using GLMM with a Poisson distribution and logarithm as ...
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LMMs: Random effects with categorical variables

I am setting up LMMs to assess the effect of two interventions on the clinical outcome (Y) over time. Thus, I have 2 predictors: group (between-persons, 2 levels: interventions A and B) and time (...
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1answer
399 views

Predictions from Poisson GLMM (lme4) lower compared to GLM

I am modelling visitor counts to a sample of sites in a forest in order to predict the number of visitors to the rest of the forest. My predictor variables are time of day (categorical), day of week (...
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10 views

How to analyse an interaction plot with categorical response and two categorical predictors that form the interaction term?

I have computed a GLMM with BACI design, having one categorical response and two categorical predictors that form the interaction term as follows: ...
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75 views

GLMM model formulation with a partial “subcondition”

I am modeling reaction times in a GLMM using the lme4 package. My data have the following structure: Subject ID Reaction times (RT) Distractor type (Type): (3 levels): moving - static - no distractor ...
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8 views

GLMM Nested ANOVA

I am trying to fit a mixed model. I am calculating genetic variance in fruitflies from two different locations. I have 10 different strains from each location. So the strains are nested within ...
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14 views

What model do I use if I have two response variables which are influenced by each other?

I conducted an experiment where I looked at measuring animals performance for a certain task. I have 2 response variables 1.success/failure at performing the task (bionomial); and 2. latency (time) to ...
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60 views

Problems with uniformity in residuals using DHARMA to check zero-inflated count glmm

very new to statistical modelling & have found lots of the existing questions and answers from this community hugely helpful. I'm running into some issues of my own now that I can't find answers ...
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Struggle to choose a model (glm, glm with qualitative variable, glmm)

I'm currently trying to fit a model on some data, but I am quite struggling. Data There are 20000 entries in the dataset. One entry is a random pick of bacteria (among a set of ~200 bacteria). The ...
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3k views

Gamma hurdle model for continuous response?

I am modelling invertebrate.biomass ~ habitat.type * calendar.day + habitat.type * calendar.day ^ 2, with a random intercept of ...
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2answers
2k views

Are $R^2$ for GLMM useful for modelers but not necessarily for readers?

The short version: 1)Are there any published critiques of the use of $R^2$ for GLMMs, in particular the popular approach of Nakagawa & Schielzeth (2013) A general and simple method for obtaining $...
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12 views

Can I evaluate additive interaction for GLMM

I am currently running a GLMM (log-link function) examining the effect of two treatments on the instances of an arthropod. I seek to determine if there is additive interaction between the two ...
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250 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: ...
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1answer
173 views

Intraclass Correlation Coefficient with Bayesian ordered-logit GLMM (STAN)

I am fitting a Generalized Linear Mixed Model for an ordered outcome, in form of an ordered logit, with random intercept and slope. For this task, I am going Bayesian by handling STAN through the ...

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