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

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Double hierarchical models using MCMCglmm [on hold]

I am new using R and I need a model to fit both the mean and the SD of the model (similar to the Double hierarchical generalized linear models). Is it possible to perform using the MCMCglmm package? I ...
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5 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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19 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
19 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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15 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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10 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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40 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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33 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
42 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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15 views

Strange predict() results from GLMMadmb after adding Zero Inflation

I am attempting to model abundance of a species based location groups and environmental parameters. I've encountered a problem with the predicted values from these models that is associated with ...
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1answer
31 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
24 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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10 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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27 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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25 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
101 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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23 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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39 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. ...
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1answer
31 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
32 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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43 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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29 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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80 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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15 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
48 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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61 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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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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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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35 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
69 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
79 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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71 views

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

I am having a hard time understanding what's going on in with my model selection, and why a model with two insignificant variables is getting chosen as the "best model" over a model without those two ...
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29 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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27 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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88 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
68 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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141 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 ...
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28 views

Confidence interval for psychometric binomial GLM model on more than one subject in R

I'm trying to estimate the confidence interval of a psychometric curve (binomial probit GLM), for a population (now only two subjects). Suppose I've subject "a" and subject "b", which performs ...
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28 views

Probit regression with misclassified binary dependent variable in R

Is there a generalized linear mixed-effects model implementation for R that could handle misclassified binary data? Unless I have overlooked something in the documentation, glmer with ...
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1answer
137 views

In what sense is the interpretation of coefficients in a GLMM subject-specific?

There is something I'm not quite understanding conceptually about the output from generalized linear mixed models. I have read that the target of inference in GLMMs is subject-specific. For example, ...
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245 views

Overdispersion and modeling alternatives in Poisson random effect models with offsets

I have run into a number of practical questions when modeling count data from experimental research using a within-subject experiment. I briefly describe the experiment, data, and what I have done so ...
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2answers
124 views

Standardize non-normal predictors before performing binomial GLMM using mean and sd?

I am planning to predict a binomial variable (1/0, a used point by an animal or point available to an animal in its range) using several continuous, distance-based predictor variables (distance to ...
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52 views

Problem running dredge function with glmmadmb model

I'm running the following model in R: ...
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64 views

How can I evaluate spatial autocorrelation in a binomial GLMM?

Following Dormann et al 2007 Ecography, I have employed a GLMM approach in R to account for spatial autocorrelation in a binomial regression model (logistic regression) that does not have random ...
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16 views

choosing the best structure of the random effects in a GLMM [duplicate]

I am trying to choose the best random effect structure in a GLMM, before starting with the fixed terms. To do that I include all the fixed effect and their interactions (beyond optimal model) and ...
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43 views

lmer, effect of a ramdom factor in a covariate [closed]

hi I am doing a General Linear Mixed Model in R, lme4 package. I want to test the effect of a random effect on a covariate, as well as on the response variable. I thin that the command would be the ...
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1answer
85 views

Do I need more than one random slope?

When constructing a GLMM in R, do I need more than one random slope if I "see" that slopes differ for multiple continuous variables? In my case, I am analysing the number of plant species (...
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2answers
181 views

Can I include covariate as random effect in glmer?

I have a question regarding covariates in a GLMM. My model comprises a condition variable and a covariate. Crucially, my binomially distributed dependent variable can be interpreted only in dependency ...
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Clear explanation of pseudo likehood

In generalized linear mixed model (glimmix) parameters are estimated using pseudo likelihood. I was trying to understand how this type of likelihood calculated. Thanks !!!