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

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What is the importance of overdispersion in GLMM?

I am constructing several GLMMs and someone suggested me to estimate the overdispersion (using overdisp.glmer {RVAideMemoire}). Why is this important, and which consequences exist when ignored? And ...
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4 views

GLMM with correlated explanatory variables

I am using prediction from GLMM to explore how two variables ($X_1$ and $X_2$) affect a response variable ($Y$). In my data these two variables are negatively correlated ($r_{X_1,X_2} = -0.24$). ...
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14 views

Using randomisation of fixed effects for a psuedo-p in mcmc glmm

I'm running generalized linear mixed models in R using the function MCMCglmm(), and with summary this generates p (pMCMC) values. However, pMCMC is, by the authors ...
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2answers
21 views

How to select automatically the best GLMM?

I have a set of 14 variables and I want to construct GLMM's. I want to include at first each variable and then add all the others, one at the time. This will require a lot of combinations of ...
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1answer
17 views

Multivariate/interaction prediction from glmm

Previously I have asked how to calculate the predicted response for groups (split by two categorical variables) given a single continuous fixed effect, in a glmm. Now I would like to take it one step ...
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5 views

prediction of Random Effect (BLUP) in unique model framework

Basic question: Is there any method that could predict the random effect in different model framework than GLMM(generalized linear mixed model)? while I was reading ...
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3answers
209 views

Can I test for correlation between variables before standardize them?

What I want to do is to construct GLMM's to evaluate resource selection, and I have a set of variables (some representing distances and others representing % of land cover). Can I test for ...
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19 views

Which assumptions do I need to check for a GLMM with a binary response (and how?)

I am modeling binomial responses using Generalized Linear Mixed Models with a nested random effect (not of interest, simply a control: year nested within location) and both categorical, count, and ...
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12 views

Question regarding variables transformation for GLMM's

I have a response variable (binary:1/0) and a set of explanatory variables, with different units: some have values in %, others in meters (distances, altitude and differences between elevation pixels),...
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10 views

Odds ratio in multivariate GLM

How to calculate odds ratio in multivariate GLM? I selected parameter estimation in option but the outcome didn't show EXP(B).
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18 views

LRT for a Linear Mixed Model

I want to compare the likelihoods for a model with population structure (a mixed effect represented by a variance-covariance matrix) to one without population structure (represented by an identity ...
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19 views

Question about application of GLMM with Poisson

I'm working on revising stats for a manuscript involving male reproductive success of deer. We measured three variables (body size, ...
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22 views

How do I report the results of likelihood ratio test from glmmADMB?

I want to test if an interaction is significant. My data are strongly overdispersed and contain repeated measures so I've a negative binomial glmm model in glmmADMB. I can compare the model contain ...
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10 views

What error distribution can I use for GLMM with continuous data but not normal due to too many 0s?

I am having problems with building a generalised linear model with random effects. I am modelling how a sensitivity ratio between various taxa and cyanobacteria (logSR) is effected by the taxa and ...
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Nested GLMMs: which are my random factors?

I am analyzing the number of seed capsules between different genotypes (A,B and C) I have 4 replicates for each genotype and in each of these replicates, I have 8 plants. Here is an example of the ...
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1answer
31 views

Random slopes for interactions without random slopes for main effects?

I have a GLMM with the following form: m1 <- glmer(Y ~ A*B + (A*B|Subject), data, family=binomial(logit)) where A and <...
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30 views

Beta binomial GLMM dispersion statistic issue

I am analyzing proportion data with GLMM in which the number of occurrence a behaviour of interest has been displayed and has not been displayed are concatenated and fitted as a single response ...
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16 views

How to apply multiple random (clustered) factors in HGLM package? And how to solve Cholmod error: wrong dimensions? [closed]

I'm working on alien reptiles on Mediterranean Islands. The idea is to assess which variables are influencing/favouring reptiles introductions, which reptiles are being introduced and which island are ...
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53 views

Variance Partition Coefficient and R²GLMM(c)

After computation of one model many times with GLMM (the DV has 3 values / I compute the model for the 3 values and for 26 different cohorts separately) the results at first were no surprise: In the ...
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11 views

Using variables measured at different scales in a binomial GLMM with successes and failures

I have seed and seedling abundance data for several plant species. I am trying to model the effect of my treatment on how many seeds successfully transition into seedlings (seed-to-seedling ...
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2answers
96 views

Key scientific publications reporting non-normal GLMMs in marine biology

I developed Poisson and Binomial GLMMs following the steps described in the excellent book from Zuur et al. (2009) Mixed Effects Models and Extensions in Ecology with R and I'm now ready to include my ...
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1answer
58 views

Using DIC to test which data should be used - different sample sizes

I have a glmm model $y \sim b_1 * b_2 * b_3 + random$ where $b_i$ are the fixed effects. I am using DIC to compare models and select the best fitting model. I also have some options in setting up ...
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29 views

Using DIC for model selection: (in)valid comparisons

Imagine I have the following 7 glmm models where $b_1$ through $b_3$ are fixed effects. $M_1 = y \sim b_1 \times b_2 \times b_3$ $M_2 = y \sim b_2 \times b_3$ $M_3 = y \sim b_1 \times b_3$ $M_4 = ...
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24 views

Is there a limit proportion of 0 and 1 to fit binary data using glm (link “logit”)

In relation with my other question here where I observe a strange behavior of the residuals after fitting binary data using glm/glmer, I now wonder: Are there boundaries on the proportion of 0 (or 1) ...
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40 views

Residuals with glm / glmer don't have null mean

I am trying to fit accuracy data (taking values 0 or 1) using glmer and I am puzzled to observe that the residuals of the model don't have a null mean. Wasn't this the whole point of the optimization.....
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1answer
27 views

Time as random effect or fixed effect in glmmADMB

I have a longitudinal dataset where patients have a measurement with a date, currently coded as time from end of treatment (days). Now, I want to build a model. Roughly, a zero inflated Poisson model ...
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46 views

Prediction using fixed effects in glmm

I have the following generalized linear mixed effects model (mcmcglmm in R) with data based on this paper. Sex is a two level factor (M or F), ...
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38 views

How to improve the fit of a zero-inflated, negative binomial glmmADMB model

I have been trying to fit count data that is zero-inflated and overdispersed using generalized linear mixed models. My research led me to the glmmadmb function in the glmmADMB package. I am fitting ...
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1answer
44 views

Conflicting results between GLMM and Post-hoc lsmeans

I'm studying the effect of pH and cross-types on mortality of fish. Treatment is categorical (2 levels: control and low pH) and cross-types is also categorical (4 levels: parents wild male x wild ...
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1answer
37 views

Binomial glmer with data between 0-1, not count data, not normal proportion

I have a special case of a binomial glmer and I can't figure out how to properly model it. I have a random factor (1|Species) to account for differences in species....
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7 views

Long-tailed random effect posterior distribution from unbalanced design

I am using MCMCGLMM to estimate the effect of some factors on a trait. The model is constructed with $Y \backsim B*S$ to find an interaction effect of factor B (...
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16 views

Formal formula for GLMM given glmer syntax

I'm looking for help writing the formal formula for a binomial mixed model with three crossed random intercepts, one numeric fixed effect, a logit link function, and a log-transformed offset term. ...
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8 views

Multivariate regression, non-normal response variable

I am attempting to run multivariate regression model with interactions terms to understand the combined effect for categorical variables and 2 other continuous variables. My response variable is ...
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44 views

How to validate a Poisson GLMM model?

I’m using the glmer function from the lme4 package in R to model species richness adjacent ...
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14 views

Test of significance for glmer

I would like to test the effect of a treatment ("crop") on species richness. I would rather use a glm for richness as it is a kind of count data. Besides, I have a nested sampling design (5 values ...
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24 views

Expectation of y given u when it follows Poisson distribution

So I was reading Generalized Linear Models with Random Effects by Youngjo Lee, in chapter 6 about Hierarchical GLMs there's this example: Suppose $y|u$ is Poisson with mean $\mu = E(y|u) = exp(X\beta)...
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26 views

Zero-truncated Poisson model

In the theory of generalised linear models, you may use the exponential family to find the mean and variance of certain distributions. How would the mean and expectation of the zero-truncated Poisson ...
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19 views

Use of weights in PROC GLIMMIX

I am looking to implement a generalised linear mixed model in SAS using PROC GLIMMIX. The data is from a survey, and a single ...
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16 views

Constrained regression for binary dependent variable

I would like to discuss the methodology for the following case: I have a data for several patients over several years for 5 factors describing the health of a particular patient. Every factor ...
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18 views

Variance explained $R^2$ by separate fixed effects (and interactions)

I am currently assessing the effect of five environmental variables (A, B, C...) on a trait (Y). I would like to estimate how much variance in Y each environmental variable explains. Previously I had ...
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1answer
33 views

Does non-response bias affect the validity of a statistical model?

I want to build a (generalised linear mixed) model on some survey data. The PROC GENMOD command in SAS doesn't admit weighting in the sense of survey weights. I am not interested in population-level ...
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14 views

single group pre/post test

I have a single group pre/post test design. I am estimating a GLM with baseline covariate, along with a vector of other covariates. The goal is to assess change in the outcome. I found a significant ...
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1answer
101 views

Help with zero-inflated generalized linear mixed models with random factor in R

My study has a complicated design and I am not sure if I am modeling my zero-inflated data correctly. I have seed abundances and seedling abundances for 11 species. I have one main "treatment" with ...
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12 views

Strange predictions from binomial glmm?

I am analysing the dominance of a Species, i.e. its relative abundance in a community. Since these data are proportions I use binomial models. However, the predictions from these models are ...
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28 views

How to interpret glmmPQL summary value

I'm doing a GLMM with quasi-Poisson to check for a spatial correlation between some predator bugs and their prey (count data of predator and prey + added distance of plots). I've added everything into ...
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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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1answer
26 views

Quadratic term and categorical predictors

I have a quick question about the use of quadratic term in GLMM. Can I use it with categorical variables? I read somewhere that its use is restricted to continuous predictors and the thing is that I ...
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1answer
45 views

Confidence bands for model averaged predictions of GLMMs

I use R with the MuMIn package for Multimodel inference. my global Model is ...
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25 views

Nested random factors in GLMM: use them or drop them?

I am a new R user running into GLMM models. I have some data of frequency of pollinators in crop fields adjacent to forest fragments, with the following experimental design: 4 forest fragments, 2 of ...
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93 views

Alternative to GLMM for normalised ratio (Bounded: -1 to 1) response variable

My response variable is a metric calculated from the normalised ratio of two variables. Calculated as (a-b)/(a+b), resulting in a normalised ratio of continuous data bounded between -1 and +1 - my ...