2
votes
1answer
14 views

conducting multi-level regression on ordinal DVs with imputed data in R

Do you know of an approach/package that facilitates mixed model regression of ordinal dependent variables on multiply imputed datasets in R? Ideally, the function takes: a list of multiply imputed ...
0
votes
0answers
22 views

R² (squared) from a generalized linear mixed-effects models (GLMM) using a negative binomial distribution

I try to compute the marginal and conditional R² for a GLMM using a negative binomial distribution by following the procedure recommended by Nakagawa & Schielzeth (2013) . Unfortunately, the ...
1
vote
1answer
14 views

Calculated breeding values using markers using animal model in R

Animal model (frequently used in animal science and sometime in human or plants) is mixed model with: $y$ = $X$$b$ + $Z$$u$ + $e$ y is observed values for any quantitative variable, $Xb$ is fixed ...
0
votes
0answers
16 views

center variable separately for each factor in linear mixed model?

I am working on a relatively simple mixed model where I have two continuous predictors with an interaction term and three sites. I am treating the two predictors as fixed effects and the site as ...
1
vote
1answer
39 views

Multivariate model in lme() with independent random effect, similar to MCMCglmm

I would like to specify a multivariate model with lme with a random effect for group which is independent across variables. I found this post, which explains that ...
3
votes
0answers
41 views

Mixed effects modelling; what to do when model is over-specified?

I'm trying to use mixed-effects modelling to analyse some data. There are a number of variables that I need to specify within the model, two of which are between-participants (...
2
votes
2answers
57 views

What is the right way to analyze a nested design in R?

I know that there are already a host of questions about nested designs but many of them haven't been answered or come from biological domains which I sometimes find hard to transfer to my domain. I ...
0
votes
0answers
28 views

How to model non-linear time courses with nlme

I have some time course data which plotted looks like this: I am trying to fir a model to it using nlme.lme(). I am interfacing with R via RPy, and using the ...
0
votes
1answer
35 views

Repeated-measures, crossover analysis using linear mixed model in R

I have a data set that I am attempting to analyse in R and I am relatively new to the environment. My full data set contains 7 subjects (represented by Subject), that all receive 3 treatments ...
6
votes
1answer
94 views

Relationship between paired t test and simple mixed model

The bounty I placed on this question expires in the next 24 hours. I have a psychological data set which, traditionally, would be analysed using a paired samples t test. The design of the ...
0
votes
0answers
45 views

Help with lmer in the lme4 package

I am new to using linear mixed models and would greatly appreciate any help I can get. I have an equation of the form $ y = X\beta + Zu + \epsilon$ where $u$ is a random effect whose covariance ...
0
votes
0answers
23 views

MANOVA for mixed model with multiple repeated measurements

I struggle performing a MANOVA for a mixed model. I have the following columns: S - subject (1,...,N) B - in between group (B1, B2) W - repeated measurement - within (W1, W2) M - measured dependent ...
4
votes
1answer
73 views

Longitudinal item response theory models in R

I'm trying to fit longitudinal item response theory (IRT) models in R. I have a test that was administered at multiple measurement occasions. I'd like to examine individuals' growth curves of factor ...
0
votes
0answers
14 views

Site effect in GAM model

I am trying to build GAM model to see the effect of several environmental variables on the total abundance of one species. I have collected samples from three sites with three replicates from each ...
0
votes
1answer
38 views

fitting LMEMs for repeated measures with no correlation between intercept and slope

For a simulation study, I contrast the power of different LMEMs for repeated measures. To get p-values, I use likelihood ratio tests where I compare a model including a fixed treatment effect with one ...
1
vote
1answer
69 views

Random factor nested in two fixed factors

I have read Random effect nested under fixed effect model in R, but I have a doubt: My data is on germling survivorship, I have Temperature as a fixed factor (2 ...
0
votes
1answer
27 views

Fitted values of 'lme' function result

I fitted a linear mixed model with R as follows. ...
2
votes
0answers
29 views

How would you model this random effects structure?

I have a sort of weird and complicated model design, and I'd like to get your opinion on how best to model the error structure. I have 100 sites, with each site falling into 1 of 4 different forest ...
0
votes
0answers
47 views

Alternative to MANOVA when group covariance matrices are heterogeneous?

I'm running into problems meeting some of the assumptions of MANOVA, namely homogeneous group covariance matrices and normality. I'm looking for an alternative approach where assumptions are not ...
2
votes
1answer
81 views

Difference between log-normal distribution and logging variables, fitting normal

Context: I have a set of data that is bimodal, so I used the mixtools package in R to fit a bimodal normal distribution to it. It looked as if the normal did not fit very well, and given other similar ...
1
vote
0answers
91 views

Post-hoc tests on linear mixed model give mixed results.‏

I am quite new to R so apologies if I fail to ask properly. I have done a test comparing bat species richness in five habitats as assessed by three methods. I used a linear mixed model in lme4 and got ...
1
vote
1answer
151 views

Coefficients from glmer in R

In a mixed effect model where the intercept is random effect and the slope is fixed effect (see the code below), I understand the output of summary(glmer(...)). But ...
0
votes
0answers
41 views

Estimated SD equal to 0 (lmer)

I'm trying to fit a mixed model of my data, but I'm getting the estimated between-subject standard deviation equal to zero. I need to estimate the between-subject standard deviation and within-subject ...
0
votes
0answers
85 views

R: glmulti for mixed models returns several best models, Automated Model Selection (multilevel analysis, hierarchical model, nested data)

I searched the entire web including this forum on some help on how to use the glmulti package in order to identify the "optimal" fixed part of a mixed model with a given random part. However, I could ...
0
votes
1answer
517 views

Warning messages from mixed model (glmer)

I ran a mixed model using lme4::glmer for a logistic regression and consistently got these warning messages. I noticed there are still regular results even so, but are they accurate estimates? ...
0
votes
0answers
25 views

Analysis of a mixed design with categorical and continuous variables

I have no idea how to do the following analysis for an experiment. For my independent variables I have two continuous between-subject variables (personality traits scores), one categorical ...
0
votes
0answers
22 views

Compare effects of paired explanatory variables within a (binomial) GLMM

I am using a GLMM to model the probability of visiting a 400m radius area. I have 135,000 observations (areas) and for each area I have the proportion of the habitat types within it. I want to examine ...
1
vote
0answers
40 views

Specific variance covariance structure in lmer

I have a dataset with cluster correlated data; multiple measurement on the same subject (not over time). I am trying to create two different mixed models using lmer in R with two specific variance ...
1
vote
1answer
73 views

AICc results in R

I used the model: ...
0
votes
0answers
31 views

How can I calculate ePCP and/or Brier scores for a mixed-effects logistic regression in R

I am trying to calculate ePCP and Brier scores in R for a mixed-effect binary logistic regression. It cannot seem to find any packages that work for mixed models. I have tried the packages OOmisc and ...
1
vote
1answer
66 views

Why isn't there random effect?

I'm trying to use lme4::glmer to fit a mixed model such like that: ...
4
votes
2answers
161 views

Is my dataset suitable for a mixed effects model?

I've been putting a lot of work over the last few days into bring mixed effects models to bear on some behavioural data I've collected for my thesis, but it's occurred to me that I'm not 100% sure ...
1
vote
0answers
45 views

Is there an R function to do a survival analysis with right censoring + nested + crossed factors

I have this dataset to model, but I'm not sure how to do it. I want to model the surviving probability of different populations of two species depending on a treatment applied. Populations should ...
0
votes
0answers
51 views

Specification of a mixed model with nesting with lmer

I've been told my model wasn't statistically correct, but I'm not sure what I should do. What I have is basically 2 species: A and B. For each species, I have 3 replicates: 1, 2, and 3 (=6 ...
2
votes
1answer
129 views

P value for interaction term in mixed effects models using lme4

I'm analysing some behavioural data using lme4 in R, mostly following Bodo Winter's excellent tutorials, but I don't understand ...
1
vote
0answers
99 views

Repeated measures mixed model using lmer in R

I’m hoping to get some guidance in specifying a mixed model using the lme4 package in R. The study is quite straightforward. It’s a repeated measures design with pre/post measurements on the ...
0
votes
0answers
23 views

How to obtain the complete model matrix of a mixed model?

Suppose I have a mixed model like this: ...
0
votes
0answers
31 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
62 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
71 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
115 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
107 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
2answers
96 views

How to predict binary outcome from a glmm model

Suppose I fit a generalized mixed logistic model such like that: ...
1
vote
1answer
268 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
89 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
39 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
95 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
125 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
47 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 ...
2
votes
0answers
202 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 ...