0
votes
0answers
17 views

Cummulative Mixed Model in R variable names

I'm trying to fit a cumulative link mixed model clmm() in Rstudio. I'm currently having issues with the diagnosing what is wrong with my model from the output I am getting. The output I got from my ...
0
votes
0answers
27 views

Cannot do Tukey test in multcomp

After performing series of linear mixed models in lme4 to justify which model with which level of interaction to be used, now I would like to do the Tukey's test for multiple comparison. So first, I ...
0
votes
0answers
34 views

Fitting non-normal data in lme4 with a family distribution

I'm currently working on fitting a model where we predict the level of some biomarker as a function of time (see image at bottom). I have two difficulties: Each person contributes 2-3 datapoints ...
3
votes
1answer
75 views

Using glmer to estimate treatment interactions

In my data, I have two treatment conditions with repeated measures for each subject. I would like to run a mixed logistic regression separately for each of my two conditions where my binary outcome DV ...
0
votes
0answers
71 views

Difficult interpreting linear mixed model result - R lme function

I'm fitting an harmonic regression model on data from different plants separately as follows: ...
0
votes
1answer
51 views

How to predict binary outcome from a glmm model

Suppose I fit a generalized mixed logistic model such like that: ...
1
vote
1answer
85 views

Binomial GLMM with categorical predictors: p-values?

My data has a binary response (correct/incorrect), one continuous predictor score, three categorical predictors (race, ...
1
vote
0answers
32 views

Binomial mixed model with categorical predictors: model selection and getting p-values [closed]

My data has a binary response (correct/incorrect), one continuous predictor (with NaNs) and several categorical predictors. I want to add a random intercept for a ...
1
vote
0answers
25 views

What plots should be used for diagnostics for linear mixed model?

Before fitting a linear mixed model, can any plots be used to show a random intercept/slope is justifiable in the model? I.e. these plots may indicate a different pattern for each individual over ...
0
votes
0answers
56 views

testing differences between levels of a factor in a linear mixed model

I'm trying to wrap my head around using a linear mixed model and appropriate post-hoc tests to determine if there is a significant difference between various treatments in an experiment I inherited. ...
0
votes
0answers
57 views

Use predicted values with or without random part to plot Residuals with binnedplot of a logistic regression in glmer (lme4 package) in R?

Which binnedplot of the glmer should I use to check the model? The residuals against the predicted values without random part(REform=NA) or residuals against the predicted values with random ...
1
vote
0answers
23 views

Calculating point estimates from model-averaged parameters

I'm using an IT-approach and multi-model inference with some count data. I have used model averaging to obtain parameter estimates from several GLMMs with Poisson-lognormal errors (Poisson family ...
1
vote
0answers
53 views

Fitting multilevel models to complex survey data in R

I'm looking for advice on how to analyze complex survey data with multilevel models in R. I've used the survey package to weight for unequal probabilities of ...
0
votes
0answers
28 views

Growth curve analysis on orthogonal polynomial terms

I am conducting a study which is looking at the effect of 'Condition' (Quiet, Intelligible, Unintelligible) on the pupil(eye) response over time. Upon visual inspection of my data plots, pupil ...
3
votes
0answers
35 views

Different estimates of crossed random factor variance using nlme and lme4

I want to fit a model with two crossed random factors that also allow heteroscedasticity. Whereas nlme4 allows non-constant error variance, I was not sure how to ...
0
votes
1answer
47 views

Cross-validation for mixed-effect logistic regression? [duplicate]

I would like to use cross-validation to test how predictive my mixed-effect logistic regression model is (model run with glmer). Is there an easy way to do this using a package in R? I've only seen ...
2
votes
0answers
62 views

Suitable method for modelling (underdispersed?) count data with lots of zeros and long tail

I have a small data set of counts of bees. I tried a simple Poisson model without random effects but it was very overdispersed (3.95). When I fit a GLMM with random effects (using glmer in lme4) it ...
1
vote
1answer
75 views

Mixed-effect logistic regression in R - questions

I am new to R, and don't see these questions answered anywhere in documentation (though I could be wrong). I am using the following nomenclature to run my mixed-effects logistic regression, based on ...
0
votes
0answers
27 views

calculate VIF for glmm

If we have colinearity among our axplanatory variables we can calculate a varianvce inflation factor to estimate the effects on our standard errors $$ VIF = 1/(1-R^2) $$ I am unsure how to calcuate ...
2
votes
1answer
94 views

Dropping term for correlation between random effects in lme and interpretting summary output

I want to fit a model without a correlation term between the random effects with lme. In lmer this is fairly straighforward.... ...
0
votes
0answers
27 views

Partitioning error in mixed factorial anova in R

I need help understanding a 3-way anova with 2 fixed factors and 1 random factor. I am analyzing an experiment looking at the effect of diet on feeding rate in snails. The two fixed factors are diet ...
2
votes
1answer
73 views

Interpreting random slopes equal to 0 using lmer in R

I have just started working with mixed models and the lme4 package and was after some advice interpreting some results. I have a data set looking at the change in nest height of birds (NAP) over time ...
1
vote
0answers
52 views

Multivariate multi-level analysis in nlme

The question I have a dataset which I think requires a multivariate multilevel analysis. I am unsure both of the appropriate model and of how to fit it with R. I ...
0
votes
0answers
51 views

Interpreting coefficients for random effects models with extremely unbalanced data

I'm currently working with a data set that has numerous samples collected over time at different sites in a study area, and I'm interested in detecting a trend over time for that area. I know that in ...
2
votes
1answer
257 views

How to fix an overdispersion in a Poisson GLMM with lmer function in R?

I want to model counts as being dependent on two nominal variables, one continuous variable (all as fixed effects) with 3rd-order interactions and one grouping variable (as random effect). However, I ...
2
votes
0answers
220 views

How to test and avoid multicollinearity in mixed linear model?

I am currently running some mixed effect linear models. I am using the package "lme4" in R. My models take the form: ...
2
votes
1answer
63 views

Multi-Level Model with two scores per level 2 unit - reasonable analysis?

I have an experimental design with attitudes toward one positive and one negative stimulus nested within individuals. I also have a continuous predictor at the person level (a personality construct). ...
1
vote
0answers
37 views

Mixed-model specification in R - exploring individual differences

My current experiment aims to explore the effect of viewing condition, difficulty and depth perception on object grasping. I'm mostly interested in the effect of individual differences in depth ...
0
votes
0answers
21 views

High value of denorminated degree of freedom mixed model in R?

There are three breeds of total 80 animals, timed with 200 repeated observations/animal; response variable is milk yield (MY), predictor is day from birth (DFC) . I performed a mixed model on this ...
2
votes
0answers
86 views

Why is there a dramatic difference between aov and lmer?

I have a mixed model and the data looks like this: ...
2
votes
0answers
65 views

Use nonlinear mixed model for binomial distributed data

I frequently use this model to test catch efficiency and size selection properties of a given trawl fishing gear: \begin{equation} \theta(l)=\frac{s\times r(l)}{(1-s)+s\times r(l)} \end{equation} ...
3
votes
1answer
108 views

A statistical model for a sample of independent networks

Based on the lack of responses to my previous network question, perhaps this is not quite the place to ask this question, but I'll give it a try. I am planning a series of studies that involve small ...
0
votes
1answer
207 views

Interpreting intercepts in mixed effect model with categorical predictors

Trying to fit a linear mixed effects model with 2 categorical predictors (group & worker) where worker is a random effect and group a fixed effect. I'm trying to figure out 1) whether I should ...
0
votes
0answers
39 views

Repeated measures mixed multinomial model in R - extract coefficients

I would like to perform repeated measures mixed multinomial model using R. To be exact I would like to do MaxDiff analysis similar to SawTooth Hierarchical Bayes method. I want to use mixed models ...
3
votes
2answers
156 views

How to deal with unbalanced group sizes in mixed design analysis?

I have 2 x 2 x 2 mixed design with two between subject factors (sex, organizer) and one within subjects factor (task). The group sizes of the 'sex'-factor is unequal. When I perform a factorial ...
1
vote
1answer
198 views

How to determine effect of random factors and slopes and their variance in Mixed Model

I would like to determine the variance explained by random factors and slopes in a mixed model but am unsure if the analysis I use and my interpretation are correct. Furthermore, comparing models and ...
1
vote
1answer
607 views

Mixed effects model validation and selection with `lme4::glmer`

If I had a glm using on count data I may do the following: glm(response ~ exp1 * exp2, family = poisson, data =data) The ...
3
votes
1answer
142 views

glmm unbalanced nested random factors

imagine you have the following data structure ...
2
votes
3answers
873 views

Checking assumptions lmer/lme mixed models in R

I ran a repeated design whereby I tested 30 males and 30 females across three different tasks. I want to understand how the behaviour of males and females is different and how that depends on the ...
0
votes
1answer
92 views

Mixed model fitted on time course data

I have some time course data which plotted looks like this: I have fitted a mixed model to my raw datapoints with R's lme4::lmer, as seen in this code. In ...
0
votes
1answer
62 views

How to fit a mixed model to this advertising data?

I have data on about 20000 consumers who were exposed to some form of advertising. The data is in the following form. ...
6
votes
1answer
361 views

Why can't I match lmer for family = binomial?

I'd like to match the outputs of lmer (really glmer) with a toy binomial example. I've read the vignettes and believe I understand what's going on. But apparently I do not. After getting stuck, I ...
2
votes
0answers
65 views

Correct model to use in travel speed analysis

I am attempting to analyse downstream travel speed of fish within two different rivers, however, I am getting lost on which model I should use. Please see working below data: ...
3
votes
1answer
90 views

Mixed-model or not? Case-study in R

I performed some observations of clownfishes. For each individual fish (each observation), I recorded the anemone species where it lives, the size of the anemonea and the size of the fish (and many ...
3
votes
0answers
94 views

Analysis of longitudinal data with very few points

I'm trying to analyse some data I've recently gotten my hands on, but I'm not entirely sure which model to use. One suggestion has been a Mixed Model, Repeated Measurements ANOVA, but I'm not sure if ...
1
vote
0answers
71 views

Calculating effect size variance from adjusted means (or least squared means)

I have a question related to this post regarding the calculation of the variance of an effect size. In my specific case, I would like to calculate the effect size and its variance from adjusted means ...
0
votes
0answers
87 views

How to do linear mixed effects modeling with this data?

Study Design: Below is a clinical trial in a longitudinal dataset. All subjects (n=34) attended V1 (baseline) and then they were assigned to either a ...
0
votes
0answers
49 views

Dramatic changes in the results from glmm with slight changes in dataset

I am running a GLMM in R using the glmmPQL code from the MASS package. I have been getting a convergence error from the following code. ...
4
votes
1answer
125 views

GLMM model specification help gender effects + an effect that is nested only within female

Main question: "What are the contributing variates to daily movement distances?" Specifically my question today relates to: "What is the contribution related to gender, and then within female what ...
3
votes
1answer
118 views

How to deal with collinearity in lme with categorical IV with > 2 levels

I'm analysing data from our experiment. We had participants in 4 groups, each participant was measured 4 times. We measured cortisol in saliva, so it leads us to the linear mixed models, because the ...