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

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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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12 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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19 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 ...
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6 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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12 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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7 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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30 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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13 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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22 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) = ...
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43 views

Interpretation of fixed effects means from glmm

I have been looking at this paper (Garratt et al 2015) and have decided to use it as inspiration for practising statistical analysis. It is a study of two populations ("P1" and "P2"), performed over a ...
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25 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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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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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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31 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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13 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
62 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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10 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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15 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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14 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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25 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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36 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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23 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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1answer
92 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 ...
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32 views

Linear Mixed Effects Model [closed]

I have data with some of the following columns: Site (categorical, 1-4), Species (Categorical, 1-21), Damage (continuous), and Age (categorical, 0-6). Age represents the visits to each site where I ...
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1answer
42 views

glmer() error: response is constant

I am trying to run a GLMM for a resource selection analysis using the lmer4 package in R. The model contains a binary response (used/unused), five continuous variables (distances to features), and a ...
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How should I interpret/follow-up on mixed logistic regression (GLMM) diagnostics?

I have experimental data (n subjects = 64) in which the response variable, accuracy (0 or 1), was measured 9 times within subjects. My predictor is Condition (A vs B) measured between subjects. I ...
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Under-dispersion in a GLMM with Bernoully outcome

I have a GLMM for my data (collected for an urban tree research), wich include the next variables: Outcome: 1 inffected, 0: no inffected Treatments 1 and 2 (like dummie variables) T1 and T2 Species ...
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28 views

underdispersion in a binomial GLMM

I am trying to analyze data from an experiment in which I measured the learning of a colour preference in birds under two treatments. 40 Individuals were organized into 8 groups, and 4 groups were ...
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51 views

glmer with binary response variable: how to select fixed effects?

I have measured nest building (building / not building) 5 times over the breeding season and want to see if there is an effect of my treatment (treated / control). After selecting random effect with ...
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148 views

How to test equivalence of two models using MSE?

I want to compare two generalized linear mixed models (GLMM), model A and model B, which differ from their link function. More specifically, I want to test wheter these models are equivalent or model ...
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8 views

How to handle with a very small sample and unbalanced dataset? Is GLMM a good option?

I'm having some troubles in analyzing and make the most of my dataset. My hypothesis: pharmacological condition maximizes utility of the decision regardless of the context (by providing the necessary ...
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13 views

How to handle with unbalanced and small sample dataset? Is GLMM a good option?

I'm having troubles in analyzing and make the most of my dataset. My hypothesis: pharmacological condition maximizes utility of the decision regardless of the context (by providing the necessary ...
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20 views

Inverse Gaussian with MCMCglmm in R

I am trying to specify a mixed model using the MCMCglmm package/function in R. My data follow an inverse gaussian distribution, so I want to use MCMCglmm as an alternative to using an inverse ...
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86 views

GLMM or LME? Repeated measures help?

I am having trouble using the correct test and r code for my experiment. Essentially I measured insect emergence daily from artificial streams with 3 treatments.: ...
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56 views

Interpreting the residuals vs. fitted values plot for logit GLMM?

What I have is a generalized linear mixed model of the log OR of a rater (random effect) giving a response above a certain level on an ordinal scale, given a specification of what the rater was ...
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55 views

When you have a multilevel / mixed effects model, how do you incorporate the random intercepts when making a prediction?

When you have a multilevel / mixed effects model, how do you incorporate the random intercepts when making a prediction? Here is the context: I'm trying to model a Bayesian regression using an index ...
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data visualization following glmm in lmer

Everything I know about glmms is from the internet, and after extensive searching, I haven't come across a good clearcut guide for how to visualize your data in a way that is relevant to hypotheses ...
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39 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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59 views

Shall I use a random effect or not?

I need to see if in the case I am going to present it is worth to use a random effect or not. I carried out some bird counts from 9 elevated lookouts in an island. Just to orient you, these lookouts ...
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20 views

Determing Probability Distribution of PCA Values

I am trying to determine the best distribution for PCA values. I did an experiment where I have a lot of response variables and I think they're best interpreted through using a PCA. I want to use a ...
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24 views

What test to use for non-parametric repeated measures data?

I've been having trouble finding the correct test to use for my data. I measured the response of subjects to two treatments across three different time periods (e.g. beginning, middle, end). I want to ...
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58 views

Which test to use for matched case-control setting with repeated measures and a continuous outcome?

I apologize if this question has already been answered in the past; I was unable to find a similar setting by searching. I have a study with 2 groups (rare cases and their siblings, N=13+13). Each ...
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1answer
115 views

Crossed fixed effects model specification including nesting and repeated measures using glmm in R

Background: I am interested in looking at the effects that Culture, Treatment and Time ...
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17 views

Marginal vs. Conditional Model

I have a question regarding GEE vs. GLMM. I know the probabilistic difference (marginal vs. conditional). What I want to ask, is when should I use each one. More specifically, in clinical trials, is ...
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19 views

R-Side GLMM vs. GEE

I wanted to ask what is the difference between an R-Side mixed model (with a binary outcome) and a GEE ? People often call an R-Side GLMM a "GEE type" model, but it ain't a true GEE, since it has also ...
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161 views

Nested random effects in lme4 R

Background: I have data on time to infection across multiple sites across a gradient. The design involves 2 latitudes (In and Out) with sites 1 and 2 nested within “In” and sites 3 and 4 nested within ...
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1answer
59 views

Poisson glm for rank or score data?

I have a question about analyzing a dataset that I'm currently working with. Each row of the dataset represents an individual songbird, and its reproductive success over the course of a breeding ...
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43 views

Modeling Correlated Binary Data

I have data which looks like this: Subject ID (unique identifier), Group (Treatment or Control), Eye (Left / Right), Outcome (Success / Failure). The data is coming from a trial testing a new ...
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70 views

How to account for a lack of fit using a quasi-poisson on non-integer, overdispersed data

I am trying to run a mixed model on over-dispersed non-integer data. My data are not counts, but are zero-inflated and over dispersed. The variable is distance (how far a gps point is from a central ...