Questions tagged [glmm]

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

Filter by
Sorted by
Tagged with
2 votes
0 answers
27 views

Why does higher variance between clusters increase the power to detect the effect in Poisson mixed GLM?

I simulated the dataset below and I am trying to fit the Poisson GLMM with random intercepts and calculate the power to detect the effect of $x$. When I increase the variance between the clusters ($0....
treskov's user avatar
  • 542
0 votes
0 answers
21 views

GLMM logistic regression with interactions

I have been working on a mixed effects logistic regression model to analyze some data, and I'm seeking some clarification on interpreting the results, particularly when incorporating interaction terms....
Sebastian Rocano's user avatar
0 votes
0 answers
11 views

How can I fit a GLMM model to nested data? [closed]

I am a bit of a novice on R, and completely new to GLMM in general, so please forgive any stupid/obvious parts of this question. I have data representing the concentration of a specific molecule. I ...
Raul Hilder Nine's user avatar
0 votes
0 answers
36 views

Sample size calculation for generalized linear mixed models - variance assumption for the random effect

Introduction I would like to perform a sample size calculation for the Poisson generalized linear mixed model. I will leave out irrelevant details, I need to deal with clustered data and the model has ...
treskov's user avatar
  • 542
0 votes
0 answers
32 views

How to deal with under-dispersion in negative binomial GLMM?

I have some animal species. I am interested in seeing what is the relationship between the area they occupy (my response variable, p, which is a count of cells) and ...
LT17's user avatar
  • 161
0 votes
0 answers
11 views

Non-transformed Log scale response variable in LMM - which distribution to use?

I am currently modelling tea bag index results across different forest "treatments" to infer differences, effect sizes and influence of covariates. One element of these results and a ...
Eco_Analysis's user avatar
0 votes
1 answer
31 views

Mixed models - interactions or individual regression

I am using LMMs and GLMMs(where necessary) to model carbon pools between different treatments. i.e specifically intrested in contrasts. These pools are divided between different groups e.g. diferent ...
Eco_Analysis's user avatar
1 vote
2 answers
50 views

Model selection for glmer in R

I am trying to make a model for the different amount of species caught in different traps in 3 different locations on 3 height levels, along with 3 transects per location (resulting in 9 traps per ...
Fréderick Lescouhier's user avatar
0 votes
0 answers
18 views

Missing predictor variable in GLMM.nb outcome

After running the model: ...
Adrianna Elihu's user avatar
0 votes
1 answer
36 views

GLMM with negative binomial- narrowing down variables & choosing a model

I'll start by saying apologies for perhaps not wording things correctly, as stats is not my first language (lol). Please let me know if there is any other info I need to provide to make this easier to ...
Adrianna Elihu's user avatar
0 votes
0 answers
14 views

Handling Nested One-Level Random Effects in Linear Mixed Models in R

I am constructing a statistical model to examine the relationship between thrust force and kinematic data collected from tags attached to animals. The data is structured with 'slip' as a random effect ...
user avatar
0 votes
0 answers
20 views

Model failed to converge (gamma model, self-paced reading data)

I'm trying to run a Gamma analysis in a self-paced reading data. However, the model successively fails to converge. I've seen some answers here trying to solve this problem for other people, but none ...
user avatar
5 votes
1 answer
209 views

Visualization of a mixed effect logistic regression model?

Can you suggest me which graphs I should do to visualize a mixed effects logistic regression model with three fixed predictors (all categorical) and two random intercepts?
Katherine's user avatar
  • 165
1 vote
0 answers
11 views

Finding covariance structure for Bernoulli GLMM (Random Intercept)

How does one find the covariance structure theoretically for a Bernoulli GLM? For Normal LMMs ($y_{ik} = x_i^T\beta + \epsilon_i + u_k$) it's quite straight forward. For observations within the same ...
Maverick Meerkat's user avatar
1 vote
0 answers
23 views

Choosing different random effects structures for mixed-effects models with multiple response variables in R

I'm working on a project where I have two response variables of animal behaviour: one is count data (Poisson distribution), and the other is proportion data (Binomial distribution). I constructed GLMM ...
Paritosh ahmed's user avatar
0 votes
0 answers
18 views

Effect size with GLMM gamma distribution

In response to a previous question posed about effect sizes with a generalized linear mixed model with a binomial distribution, it's been clarified that estimating effect sizes is not straightforward. ...
kfin's user avatar
  • 1
0 votes
1 answer
26 views

glmer problems in seeing all variables

I am trying to run a binomial glmm to understand the relationship between various concentrations of a compound sensed by different castes of ants. We have 5 different compound concentrations (a-e), ...
Allyssa Hinkle's user avatar
3 votes
1 answer
91 views

Added more data and suddenly GLMM fails to converge (R)

I have a dataset where I randomly sampled housing developments, and then within these I systematically sampled every habitat patch. I now have a dataset where each observation is a patch_ID, and I ...
sirianmckellan's user avatar
1 vote
1 answer
63 views

How do I prioritise model diagnostics while considering model selection and parameter uncertainty?

I have fitted a generalized linear mixed model using glmmTMB on the data (110 observations, balanced data) collected from an observational study to understand the ...
medium-dimensional's user avatar
0 votes
0 answers
15 views

Meta-analysis of Kaplan-Meier survival estimates from one-arm studies

I am writing this topic because there is a statistical problem which does not let me sleep at night. For introduction, I am a clinical researcher interested in niche fields, and many of my projects ...
Mały Mi's user avatar
2 votes
0 answers
26 views

regression analysis, time series analysis, or glmm?

I have a sample of individuals for each of two treatments measured across several days (different individuals for each treatment, but the same individuals within treatment across days). The pattern I ...
Bernie's user avatar
  • 21
1 vote
0 answers
43 views

Power analysis compatible with package glmmTMB

I am trying to conduct a power analysis on the following model: NativeAntModel <- glmmTMB(NativeAnts~ Treatment + Month + (1|Site), data = NativeAntData, family = t_family) Background on the data: ...
kira's user avatar
  • 11
0 votes
1 answer
416 views

Error: PIRLS loop resulted in NaN value in GLMM (glmer) model with Gamma distribution

I have a problem fitting a GLMM model with a Gamma distribution (my outcome variable is strictly positive and right-skewed) and an identity link using glmer in R. ...
Maeldun's user avatar
1 vote
0 answers
135 views

GLMM for percentage response variable

I have a completely randomized block design with 4 treatments and 3 replicates per treatment (12 parcels). Each replicate is placed within a block. In each parcel I have measured the number of ...
GiorgioS's user avatar
6 votes
1 answer
65 views

Discrete Proportion data -GLMM, regresion beta or multinominal logistic distribution

I have an experiment that have nine treatments consisting of three strains with three different levels of application. Each treatment involves 20 plants, and measurements were taken at three-time ...
Sebastian Rocano's user avatar
0 votes
0 answers
27 views

How to determine cut-off value for binomial glmm?

I have a dataset composed of an urbanization index (continuous variable) for multiple host species (random effect). I want to determine if there is a relationship between urbanization and disease ...
Amanda Goldberg's user avatar
0 votes
0 answers
26 views

Linear Mixed Models or Structural Equation Modeling, which one to use?

I am currently trying to figure out whether to use LMM or SEM (or something else?) for my longitudinal mediation study (3 time points). I want to investigate the effects mentioned below, and I am ...
Laura's user avatar
  • 1
0 votes
1 answer
24 views

Is the GLM a good fit or should I use a non-parametric test?

I have been having trouble interpreting my data of seedsets of flowers. I have gathered data from seven flowering species in four different elevations. Not all the species appear in every elevation ...
Dominik Anyz's user avatar
3 votes
1 answer
66 views

Solutions to a 'singular fit' in generalized linear mixed-effects models

What are common causes of a 'singular fit' in generalized linear mixed-effects models (GLMMs), especially when including random intercepts for grouping variables? When using the ...
Wagathu's user avatar
  • 189
0 votes
0 answers
16 views

Does multivariable quantile regression model with mixed effects require fractional polynomials for independent variables?

Hello Cross Validated community, I am currently working on a project involving a multivariable quantile regression model with mixed effects, where the objective is to explore the relationships between ...
Mikołaj's user avatar
  • 141
1 vote
0 answers
49 views

Distributional choices for sparse 0,1 data

I am using GAMs to model the relationship between a binary response variable (0 or 1) and several continuous fixed and random explanatory variables. It seems that a binomial distribution is the ...
Andrew 's user avatar
2 votes
1 answer
23 views

Record all influential factors even at high n?

my task is to evaluate the effect of a fish predator (otter) on fish abundance in natural waterbodies. While otters are found in one part of the country already in good abundances, a quick expansion ...
Cyber_phil's user avatar
0 votes
0 answers
25 views

Interpretation of summary() and anova() results in R [duplicate]

I am having some trouble understanding the difference in use of the anova() function and summary() function. For context, here is what I am working on: I am using GLMMs: ...
Manon Obdeijn's user avatar
0 votes
0 answers
22 views

Fitting GLMM using lme4 package, fitting algorithm

I'm a little confused here. So I'm using glmm model to fit user/item interaction. If user #12 liked movie #15 it's 1 otherwise it's 0. Here is my model:  ...
Efecan Bahcivanoglu's user avatar
0 votes
0 answers
36 views

Interpreting results from a glmm (lmer) with multilevel and interaction fixed variables

I am running my GLMMs on R to test whether the effect of breed on the acoustic parameters of meows is dependent on sex levels (sex*breed) and to test whether the ...
Alice 's user avatar
0 votes
0 answers
15 views

Resolving heteroscedasticity in Gamma GLMM glmmTMB

I am investigating the effect of predictor variables population.size (continuous), farm.type (categorical) and control measure y.n (binary) on my response variable outbreak duration (continuous). I ...
Tamsin Harper's user avatar
0 votes
1 answer
66 views

Linear Mixed Models: Testing the significance of a random factor using ranova() on the ouput of lmer() in R

We have a dataset with a response (dependent) numeric variable called "CTIR", a fixed (non-random) independent/explanatory numeric variable called "Temperature" and a random factor ...
user avatar
2 votes
1 answer
44 views

How to account for yearly variation in data both between and within individuals in R (lme4)?

I'll try to make this as brief as possible. I am working with binomial attendance data (0 = absent, 1 = present) for seabirds at a breeding colony. There are ~300 birds that contribute ~60 days of ...
NeedHelpWithR's user avatar
0 votes
0 answers
26 views

What Glmm method is best to analize Mortality Rate as a response variable

I am investigating the effect of two explanatory variables (one continuous and one binary) on my continuous response variable (Mortality rate). This variable is a proportion and resembles a gamma ...
Tamsin Harper's user avatar
3 votes
0 answers
89 views

Simulating a (simple) robust mixed-effects model to calculate DHARMa residuals

I am planning to simulate a mixed-effects model fitted with robustlmm::rlmer to validate if the model is correctly specified or not by using ...
medium-dimensional's user avatar
7 votes
2 answers
125 views

How can I get a best model? An exploratory LMM

I'd like to inquire about the linear mixed model and its application to my dataset. The dataset comprises a dependent variable (DV) denoted as V, alongside three ...
TKw's user avatar
  • 71
0 votes
0 answers
44 views

What model to use with repeated measures of count data and a between subjects factor?

my design is pretty simple. I have two groups (control and clinical) that play a computerized ball-tossing game in which they are excluded at varying rates by 2 computer players. There are 5 different ...
Deevy's user avatar
  • 11
4 votes
1 answer
115 views

Randomized blocking design and Mixed Models

I am developing a research project where we are evaluating the growth of seedlings. The plots are distributed in an open greenhouse and some environmental parameters vary according to their position. ...
Graciliano Santos's user avatar
1 vote
1 answer
48 views

GLMM on proportion data based on counts

I am running a GLMM on my small dataset ($n=31$) in a repeated measures study that has $2$ groups and $5$ conditions (conditions are fixed for everyone). I am interested in main effects of group and ...
Deevy's user avatar
  • 11
0 votes
0 answers
68 views

Residuals assumptions in glmm not verified! Help

I am trying out GLMMs models to test whether two categorical variables (species and sex) and their interaction (sex + species + sex*species= fixed factors) influence certain acoustic parameters (...
Alice 's user avatar
3 votes
1 answer
58 views

When should grouping variables interact in a mixed-effects model?

I was reading this post which is relevant to a research project I'm working on now. I think that I understand the difference between crossed and nested random effects, e.g. as described here. The ...
wzbillings's user avatar
2 votes
1 answer
113 views

Modeling or data error causing large standard errors in GLMM (lme4) with repeated measures

The aim: I am trying to investigate the difference of COPD incidence in participants in stratified age groups of alcohol consumption debut. The dataset: I have a dataset of approx 4700 participants ...
Mathias Therkelsen's user avatar
3 votes
1 answer
58 views

What to do when the residuals of a general LMM are non normal and a generlized LMM will not build, when is it just too non-normal?

I've been having no luck building a general LMM. The residuals are not normally distributed, they follow somewhat of a leptokurtic distribution and homoskedacity is also present. Using log ...
user3256536's user avatar
0 votes
0 answers
35 views

GLM or GLMM design for different tasks

I am conducting a study involving 70 participants diagnosed with Mild Cognitive Impairment (MCI) and 75 without MCI. All participants were engaged in taxonomic semantic, thematic semantic, and ...
Franco Ferrante's user avatar
8 votes
2 answers
138 views

How can I use a variable as a covariate which exists only for specific range for some clusters/groups?

I want to know how to use Poisson GLMMs when we have unequal samples available for different groups/clusters/participants in data. Imagine a study where each of the 60 participants are given 1000 ...
medium-dimensional's user avatar

1
2 3 4 5
21