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

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How can I find the variance components from a MCMCglmm output?

I have a dataset in which birds (n=55) were measured twice for five different behaviours. I am now trying to statistically test if individuals are reapeatable/consistent in their behaviours or not. I ...
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15 views

GLMM test P-value and inference

I am analyzing results of my artificial predation experiment using GLMM (glmer in R) where response variable is count and predictor variable [a-categorical factor with 2 level;b-categorical factor ...
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24 views

dataset is significant or not

After running the GLMM in R I got results like this: ...
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27 views

Problem fitting Poisson GLMM with observation level random effect

I simulated count data with an observation level random effect, then fit a Poisson-family GLMM using lme4. The random effects estimated show a strange pattern when ...
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76 views
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Notation of MCMCglmm for multinomial multilevel models

I want to estimate a multilevel multinomial logit model but I am struggling with the terminology and notation used by the R-package MCMCglmm. There is documentation ...
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18 views

Does something justify using bglmer to correct the warnings I got with the glmer

I conducted a risk factor analysis for which I got some warning messages. Data: bf= if the piglet got the disease=1 if the piglet didn't=0 y= year (categorical data) SOW= random effect of the ...
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1answer
32 views

Proper use of model inference (AIC) (Burnham and Anderson) - when to explore more models

I am starting an analysis, for which I have a binomial response variable (species relative abundance) and continuous predictors (habitat variables). I have done some data exploration, and there is ...
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7 views

3 groups, 3 measurement points, poisson distribution, baseline difference: GLMM or RM ANCOVA?

I have a small experimental data set. 3 group (n's = 12, 12, 16). T1 is baseline before intervention. T2 post-intervention, T3 follow-up (times between testing vary). The DV is count data that fits a ...
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6 views

Analyzing specific factor combinations

Is there any way to isolate specific treatments and test those for differences within an overall multi-factor model? I'm running a multi-way ANOVA. For my particular model, I have factors with ...
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1answer
26 views

Confusing LSMEANS results

I am having trouble interpreting results from a multiple comparison test. Here is the model I ran: ...
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0answers
13 views

Interpreting GLMM estimates

I'm trying to get my head around a GLMM with 3 categorical predictors each containing 2 levels and the outcome variable is binary (i.e correct|incorrect). I specified the 20 people as random effects. ...
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45 views

Using simulated data to check when patterns in GLMM residual plots are acceptable

I have run the following Poisson GLMM: ...
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64 views

Best way to account for time lags in logistic regression (GLM or GLMM)

I am trying to determine the best, most conservative way to account of time lags in a logistic regression type analysis (a generalized linear model with or without mixed effects). I am working with ...
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9 views

Intraspecific variation in MCMCglmm

I want to use MCMCglmm to account for phylogenetic autocorrelation on my GLMM. However I have more than one trait measurement for certain species. Is there a way ...
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30 views

Testing robustness of a model glmmadmb

I would like to test the robustness of a model I made, as the summary does not feel understandable enough to me. Let me explain: I have a large dataset of conflicts with bears in Slovenia, and I ...
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1answer
79 views

Interpreting GLM Interaction Contrasts in R (using glht)

I am trying to do a BACI analysis on count data, and I am having trouble interpreting the output from multcomp::glht. I don't understand how the contrast's coefficients are related to effect size ...
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16 views

syntax rules for specifying multiple random effects in lme4 [duplicate]

I’m trying to get my head around the lme4 syntax for multiple random effects. I know there is lots of information out there on the topic, but I still haven’t found a source that provides clear ...
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12 views

Generalized linear models - Generalized linear mixed models

I am using R and I have to perform a binomial GLM with random effect. The only problem is that I have too many predictors and also some significant interactions between them. The model is very large, ...
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51 views

Why the poisson regression and negative binomial regression gives totally different results?

I have the data of blue sheep density in 55 survey units which is watersheds. I want to test what factors affect blue sheep density. I used blue sheep count data in each watershed and log(area of the ...
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42 views

Multilevel (Hierarchical) Models - data set example

I am currently trying to find an example that will use a Miltilevel/Hierarchical Model. The data set I am currently looking at is student "success" in a post-test regarding STD education. The data has ...
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1answer
51 views

Rejecting Null Too Frequently in Poisson GLMM (lme4, glmmPQL, glmmadmb)

While trying to determine power for a Poisson GLMM, I started by checking the probability of rejecting the null for a given parameter when the null is true (parameter is zero). I kept coming up with a ...
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30 views

GLMMadmb boundary issue after including interaction term

EDIT 02JUN2015: I've realized that I framed this question focusing on a symptom of the issue and that is probably why I didn't get an answer. A closer look at the model has led me to what I believe ...
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1answer
39 views

BIC in Item Response Theory Models: Using log(N) vs log(N*I) as a weight

In IRT software packages and in the literature it is common to calculate the BIC as $$ \mathrm{BIC} = -2 \cdot \mathrm{logLik} + \log(N)\mathrm{Npars} $$ where $N$ is the number of rows in wide ...
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1answer
32 views

When fitting a GLMM, is the predicted value for any success or all successes or what?

I am relatively new to multilevel modeling and have just been given an assignment that uses a generalized linear mixed effects model. The outcome is smoking status (1=yes, 0=no) measured at three ...
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24 views

Cross validation before or after stepwise modeling [duplicate]

I have a dataset of 1931 observations and I intend to predict a binary outcome out of that. There is a list of 128 predictors (both binary and continuous). First I ran logistic regression modeling ...
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16 views

General advice on modeling clustered data

I have biomass data from ~100 sites which I wish to relate to site environmental characteristics, and then based on those relationships predict biomass (gm2) across synopic layers of surrogate data in ...
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33 views

Partially paired data, what kind of analysis to use?

I am struggling to figure out what kind of test to use for this analysis. I have 2 populations of hosts and parasites (two locations, A and B). I tested for host preference of parasites toward host A ...
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28 views

Variance component model for longitudinal data

I have a dataset with fixed and random effects, sampled over time (body phenotypes under fixed stimulations). Generally speaking, I'd like to construct a variance component/ partitioning model to ...
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2answers
133 views

GLMM validation: weird qq & fit vs residual plots

I'm encountering problems with the results of a glmer model (lme4-package). Im trying to answer the question, whether a beaver ...
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36 views

Estimating latent probability variables from binary response data (logit GLMM)

Question: How can I calculate the standard error of an estimate derived from two coefficients of a logit GLMM? We're studying the effect of a categorical condition ('volume', 3 levels) on two latent ...
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49 views

Can complete separation between a continuous predictor and a random effect cause failure to converge in a logit GLMM?

I’m running a logit mixed-effects model on binary data with a 2x2 within-subjects design, with subjects and items as crossed random effects, and the two independent variables deviation-contrast coded. ...
2
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1answer
40 views

confidence intervals around lines from glmer in lme4

I have spent a large amount of time trying to figure out how to generate a desired plot, and was wondering if any one can help. The plot is to illustrate an interaction between 'time' and 'group' on a ...
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1answer
47 views

Generalized linear model with random effects for skewed data

I'd like to use SPSS Generalized Linear Model to analyze a dataset of insects collected from one particular species of vegetables. I have following variables: NUMBER (number of insects collected) ...
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49 views

Marginal and Conditional $R^2$ for GLMM

I am trying to calculate $R^2$ (variance explained) for a set of data using GLMM's, and . Here's some dummy data. ...
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34 views

glmm for complete randomized block design with repeated measurement

I want to analyze count data from a complete randomized block design using a glmm. Observational plots are organized in 2 blocks. Within these blocks I have 5 different tratements which are replicated ...
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123 views

Error when using mixed function in afex package on GLMM

I have been using lme4 in order to fit an overdispersion model and GLMM to my data as shown below. This seems to work fine. ...
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18 views

Distribution-specific variance component to use with R-squared for ordinal logistic GLMM

I think this should be straightforward, though I cannot find an answer after digging around a lot within work by Nakagawa et al. on $R^2$ values for GLMMs. My question is similar to that posed before ...
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1answer
71 views

Translate glmer (lme4) model specification into MCMCglmm

I am having some computational trouble estimating the following model with the glmer function in lme4: ...
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73 views

Quasipoisson or negative binomial glmm with differing dispersion by group

I have a set of count data, which look something like this: ...
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23 views

Is GzLMM with linear linking function identical to (G)LMM?

Should I hesitate to report a "generalized linear mixed model with linear linking function (and assumption of a normally distributed target)" as simply a "(general) linear mixed model" in a ...
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17 views

Accounting for initial values of reponse variable in binomial GLM

R v.3.1.0. Mac OSX 10.9.5. Can somebody please recommend a method to account for initial values of a response variable in binomial GLMM? I am designing an ecological experiment, and am having a hard ...
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53 views

Zero-inflated mixed models with two-stage fitting

Zero-inflated models have a count component (Poisson/Neg. Binomial) and a zero component (logistic regression part). glmmADMB supports the zero-inflation feature but only through estimating a ...
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1answer
110 views

Model selection: can I compare the AIC from models of count data between linear and poisson models?

I am modeling count data (with offset / exposure parameter). My modeling strategy is use of a Poisson model and a negative binomial regression model. I compare model AICs, which are about -760 for my ...
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1answer
93 views

Computing repeatability from overdispersed zero-inflated negative binomial GLMMM in R

I'm trying to compute repeatability of a count response variable from a Generalized linear mixed model with multiple fixed effects and individual ID as a random effect. I'm dealing with both ...
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132 views

GLMM with 2 insignificant variables has lower AIC or BIC compared to same model without those variables…?

Background This post has been heavily edited from its previous version (three months ago). I am investigating habitat selection of 35 territorial wolves over several years of denning seasons (41 ...
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40 views

How to analyze nested, repeated and unbalanced questionnaires where the outcome is binary?

Background: My data was collected once a year for 6 years using the same questionnaire. All responses have a person-specific ID. 18 554 responses from 5 654 unique persons were collected from 7 ...
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34 views

How many random effects to specify in glmmADMB?

I am not sure if I could use 4 random effects in a glmmADMB model. According to Bolker et al. (TREE 24: 127-131, 2009) when there are more than 3 random effects MCMC should be used. However, I do not ...
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105 views

Can I get some help writing a full model? in R, using lme4, glmm, with overdispersion

I'm trying to see how treatments affect species call counts at different locations. But I am not sure what model formula I need to use. My data is organized in an excel file and looks like this: ...
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1answer
75 views

MATLAB2014b `fitglme` causes error on intermediate results

((This post is a duplicate from Stack Exchange as there was no response there)) MATLAB R2014b's library function fitglme is acting up. It seems to be producing ...
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171 views

Explained variation ($R^2$) from MCMC glmm - Nakagawa & Schielzeth 2013

This is a follow up to a question I asked previously, where I suggested that variance-covariance matrices could be used to derive correlations, which are then usable as estimates of how much each ...