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

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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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Design constraints for modelling random effects

Consider an experimental design for a target finding study in a computer environment with three factors: display size (small, medium, large) noise (small, medium, large) presentation method (A, B, ...
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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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39 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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8 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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50 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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58 views

R Mixed model for disease severity over time

I have 2 replicates of an experiment testing 4 chemical treatments for accelerating the visibility of a disease severity (y) in fruits (5 fruits/treatment). Identification of experimental units are ...
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17 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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15 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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16 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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68 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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13 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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12 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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113 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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32 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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28 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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31 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 ...
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modelling costs with meglm: error message on zero values

My dataset has repeated observations on patients with patient-level costs captured at regular intervals over a period of time. I model how these costs vary over time using time-invariant patient ...
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35 views

Interpretation of covariance estimates glmm (proc glimmix)

I am using the glimmix procedure in SAS to model a generalize linear mixed model with and binomial distribution and a logit link function. I am modeling both the G-side and the R-side covariance ...
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38 views

Set G in prior for MCMCglmm in R

I am new to the MCMCglmm package in R, and rather new to glm models in general. I have a dataset of species traits and whether or not they have been introduced outside of their native range. I would ...
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18 views

How to construct model for GLMM with repeated measures?

I'm trying to construct a model using a GLMM for my data. I performed an experiment where I exposed different subjects to 2 different treatments between 3 and 7 times (depending on the subject) during ...
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25 views

GLMM Multilevel Model

I had posted 1 year ago this post : GLMM multilevel (hierarchical) model My model is now a bit different. Nowadays I want to study the classroom, the teacher and the school effect on the pupil's ...
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GLMM or LMM with transformed data

I have a response variable that is the absolute value of a difference between two proportions. The distribution looks like this: I also have two values for each of 20 individuals, so I need to use ...
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Diagnostics for generalized linear (mixed) models (specifically residuals)

I am currently struggling with finding the right model for difficult count data (dependent variable). I have tried various different models (mixed effects models are necessary for my kind of data) ...
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Advantages and Disadvantages of GLMM and GEE

I am making a list of disadvantages of GEE and GLMM for a correlated binary outcome. So far I know that GEE requires a relatively large number of clusters, and that it produces profile curves that ...
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Which model to choose: GLMM or GEE?

I have data with a binary outcome (success/failure) and a binary explanatory variable (treatment/control). For each subject (this is a clinical study), I have two observations, coming from two eyes. ...
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23 views

Multilevel models vs GLMMs for correlated clustered data

What is the difference between the Generalized Linear Mixed Model (GLMM) and a multilevel model?
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29 views

GLMEM vs LM on proportions within random effects

I'm doing a project involving outcomes measured for people clustered within departments. The departments had previously been randomized to a treatment or control condition. One of the main outcomes ...
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GLMM for repeated longitudinal count data

I have multiple longitudinal data sets (3 repeat trials) of microbial count data for a cohort of animals (each trial had different animals); animals belonged to either a treated or untreated group and ...
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37 views

linear mixed model with 3 group categorical response

I've been looking all around the webs but cant find a conclusive answer. I have count data for a longitudinal study where subjects were grouped into three treatment groups (A,B,C) and blocked by ...
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68 views

When 2 variables are highly correlated can one be significant and the other not in a regression?

In regression, when 2 parameters are correlated and added to a model separately, how likely is it that one parameter will be a significant predictor of the response variable while the other is not? ...
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Post Hoc Test of interaction factor in binomial glmm with proportions

I've performed a binomial glmm, because my data are proportions of a species in a sample of +/- 100 Individuals. I test the interaction of two factors and use car::Anova to get the p-values. My ...
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42 views

Should I consider time as a fixed or random effect in GLMM?

I am attempting to determine if a type of pesticide is influencing the abundance of a particular species of bird. I have 35 years of data, which was collected along roadside survey routes that are run ...
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32 views

What's the difference between a random intercept and a dummy variable?

I usually work in SAS or R, so when I code a GLM with a random intercept, it's usually pretty easy. However, I've been running into a few problems (too complicated to get into here) where it might be ...
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Convergence of GLMM vs GEE

I am tring to figure out an issue which bothers me for quite some time, maybe you can help me understanding it. I wrote a SAS program to simulate the power (power analysis) for an experiment, where I ...
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19 views

Expected significance level (alpha level) for a binomial glmm using glmer()

I have data on a investigation with only three real replicates. However I have repeated measurements, that probably improve the power of the analysis. Since my response is proportional data I use ...
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15 views

GLIMMIX with two repeated measures variables

I'm new to GLMMs and want to check that I have used the appropriate syntax for my analyses. I'm analysing a longitudinal study looking at children's ('subject') behaviours ('beh') towards eleven ...
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19 views

Generalized Linear (Mixed) Modelling for different scales

I am struggling conceptually with how I can best model my dataset. My data is the abundance of spiders collected from 20 permanent traps in a forested area. These traps have been repeatedly ...
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How to interpret the overdispersion?

I fitted a generalized linear mixed model: a three-level beta-binomial logistic regression. The dependent variable is a proportion variable stemming from a limited number of trials (e.g. a value of ...
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88 views

Logistic regression on binary response or ANOVA on proportions/percentages

I am analyzing survival of seedlings in Styrofoam blocks (known as styroblocks). These blocks have a certain size and contain cavities in which the seedlings are planted. All cavities within a block ...
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31 views

Appropriate random effects GLMM analysis for mean count data? R

I'm trying to find the right way of using a mixed effects approach on some mean count data (animal visits per day to a feeder) in R. I have two interacting fixed effects (both factors) and 2 random ...
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Correct GLMM model for unreplicated factorial design

My experimental design is as follows: Three sites (Treatments) that were not replicated (Healthy Control [HC], Untreated [U], and Treated [T]). Six independent measurements (Samples) of a response ...
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Is training error ever “good enough” when we have a large enough sample?

I recently had a (more experienced) coworker tell me that when you have a large enough sample, training error should be "good enough" to assess model performance. His point was that with a ...
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Non zero average residuals on mixed effects GLM using lme4

I've ran an experiment with binary data and subject specific random effects using R's lme4 package: ...
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58 views

Convergence error in r.squaredGLMM() but not glmer() fit

I am fitting binomial generalized linear mixed effects models with 2-8 fixed continuous variables and one random effect with 8 levels. The data set has about 700 points. I am using package lme4, ...
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How to get resonable predictions of logistic models in MCMCglmm without removing the global intercept?

I am using the MCMCglmm package building mixed effect models on my data with a categorical response column (data: R1 column). My purposes are to predict the ...
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47 views

GLMM - age and time correlated

I've been trying to fit a mixed model in R however since age and time are correlated (both increase) I'm having some problems figuring out the best option. I have data on 500 children, between 2005 ...
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26 views

Categorical dependent variable - multilevel modelling using SPSS

is it alright to run a multilevel model using a binary categorical dependent variable (0,1). The model is running fine, but is there a better way to deal with it? Many thanks!
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Intraclass correlation with count data

I want to calculate the ICC between 3 different measurements where the dependent variable is a count. As far as I understood, if the data were normally distributed, I would use a repeated measures ...