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

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AICc penalising model complexity too highly?

My analysis uses a negative binomial GLMM with total revisits as the dependent variable, treatment (factor with 4 levels: 0ppb, 4.8ppb, 20ppb, 133ppb) and size as fixed effects and colony as a random ...
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26 views

Nested fixed effects in a GLMM, hypothesis testing

I am attempting a GLMM with nested fixed effects. Most examples of nesting that I see deal with random effects, but my experimental design is hierarchical by nature and I am interested in making ...
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38 views

Gamma hurdle model for continuous response

I am modelling invertebrate.biomass ~ habitat.type * calendar.day + habitat.type * calendar.day ^ 2, with a random intercept of transect.id (50 transects were repeated 5 times) My response is ...
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1answer
45 views

Problems when adding a variance structure into a GLMM

I did a GLMM model with proportional data using the lme4 package. This model has three categorical independent variables: Age (2 levels) Sex (2 levels) Status (2 levels) "Year" is the random ...
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1answer
57 views

Conditional vs. Marginal models

I have data with an outcome of 0 or 1 (binary) representing success or failure. I also have two comparison groups (Treatment vs. Control). Each subject in the study contributed 2 observations (the ...
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20 views

Obtaining significance for mixed GLMMs on count and binary data

I'm new to the software R and am trying to compute statistics on data from experiments on the offspring of lizards from two different thermal treatments - looking specifically at differences in their ...
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1answer
17 views

Methodological test for choosing 'worse' models that make 'better' (more realistic) predictions?

I've run 4 models (simple LM, quadratic model, GLMM, and GLMM with quadratic) to predict tree age (age) from tree diameter (D) for each of 42 species (SPEC). The diameter data has all been log ...
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16 views

Classifying treatment levels as categorical or continuous

I am running a GLMM where one of the independent variables is treatment in terms of pesticide concentration, with four levels: 0ppb, 4.8ppb, 20ppb and 133ppb. I am unsure whether to class this ...
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39 views

Zero-and-one inflated beta regression vs. binomial GLMM?

I appreciate some help with deciding whether I should (and how to) construct a zero-and-one-inflated beta regression model. I want to use R to test the hypothesis that there is a ...
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13 views

Determining significance of coefficients in glmer

I simply want to know how to work out the significance between coefficients in a model that is not displayed in the summary(glmer) output. ...
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22 views

constructing a GLMM in R

I am trying to build a model to find out whether different leaf species differ in their decay rates. I collected spectral measures of these leaves over time, and I now have comparisons between those ...
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15 views

Do I have heterogenity in my GLMM? And if, how do I fix it?

I'm fitting a GLMM model with overdispersion and excess zeros (using R packagae glmmADMB)and I think I have heterogenity. Here is a plot with all my IV against residuals (alls IVs reflect count ...
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1answer
82 views

How to interpret the output of Generalised Linear Mixed Model using glmer in R with a categorical fixed variable?

I have computed GLMM using glmer in R. My response variable is species richness and my explanatory variable is grazing treatment (with three categories: cattle, sheep and ungrazed). In the model I ...
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43 views

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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27 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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37 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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111 views

When and why do I have to use “trait” for multinomial multilevel models with MCMCglmm in R?

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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32 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
54 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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19 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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7 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
61 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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17 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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58 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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105 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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10 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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32 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
127 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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19 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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13 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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60 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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61 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
57 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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38 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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42 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
45 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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25 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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20 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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38 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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31 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
201 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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42 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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57 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
50 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
66 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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57 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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37 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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163 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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22 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
87 views

Translate glmer (lme4) model specification into MCMCglmm

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