1
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0answers
16 views

Specific contrasts in mixed model with interaction

I have a dataset consisting of two groups tested across three days. Therefore I run a linear mixed model as follows: ...
1
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1answer
48 views

Mixed models with R - convert from SAS code

I have this SAS code running a mixed model: ...
2
votes
0answers
23 views

R model.matrix and makeContrast. Understanding model and possible contrast

I have measurements from 12 mice, grouped in two conditions. I each mouse I have measurements from 4 tissues. The design is not balanced, 5 mice in condition1 and 7 in condition2. After reading the ...
1
vote
0answers
16 views

expected values determined with model parameters estimated from a nlme analysis

I'm kind new into nonlinear mixed model theory and I've seen that you cannot determine expected values of your response variable by simply inserting the estimated parameters into your model equation, ...
1
vote
1answer
28 views

Mixed model interaction (covariate+factor): How to interpret posthoc table output in R package phia?

In R, using package lme4, I have used the following 2 mixed models to determine I have a signifacnt interaction between a covariate (continous, normally distributed) and a factor (three levels: ...
0
votes
1answer
34 views

After trying various optimzers, model simplification running more iterations, when fitting GLMMs, R still produces warning messages

I am trying to fit GLMM's to my data using the glmer function available in R's lme4 package. The data is available at: https://onedrive.live.com/redir?resid=1B727FC7180E87DF%21118 I keep getting ...
0
votes
0answers
40 views

Mixed linear models in R, help with nested terms and procedure

This is my first post, so sorry if it not optimally written. I have a paired samples at two time points in two groups, undergoing the same intervention. I want to test the effect of my intervention on ...
1
vote
0answers
37 views

Specifying a linear mixed model in lmer with replications nested within a fully crossed design

I’m trying to specify a linear mixed model for a somewhat complicated, nested & crossed method comparison study with replicated measurements. The goal is to partition and compare variances. It’s ...
0
votes
1answer
49 views

Number of observations in groups - linear mixed effects model

I would like to fit linear mixed effects model to my dataset, but I was wondering if quantity of observations in groups matter? I have some groups with about 60 observations in each, but there are ...
2
votes
0answers
20 views

Calculating means and confidence intervals for groups with multiple observations in each subject using the NLME package in R

I need your help to identify group means and calculate the corresponding 95% confidence intervals for a set of independent samples with 2 dependent observations within each of those samples. I'm using ...
0
votes
0answers
32 views

model simplification vs post hoc significance testing of factor levels in mixed model using lme4 in R

I have fit a mixed model to describe my response variable ('Delta_mass': mass loss in g) as a function of the factor 'Trt' with five treatment levels (LL, LH, IH, HL, HH) where the first letter ...
0
votes
0answers
23 views

Calcualting R2 in mixed models useing Nakagawa & Schielzeth's (2013) R2glmm method.

I have been reading about calculating R2 values in mixed models and after reading the R-sig FAQ, other posts on this forum (I would link a few but I don't have enough reputation) and several other ...
1
vote
0answers
31 views

Multiple covariates for each fixed effect

I'm analyzing data from a classical intervention design. Subjects were divided into groups, undertaking different interventions. Each subject was measured using the same tests before and after the ...
0
votes
2answers
24 views

Convergence errors in parametric bootstraps (PBmodcomp) of lmer models

I am using PBmodcomp from the pbkrtest to perform a parametric bootstrap model comparison. However, for some of the comparisons a warning message stating that the models failed to converge appear. A ...
0
votes
0answers
9 views

analysing multiple individuals in specific time points for similarities

I am looking for a suitable analysis to examine my data for the presence of foraging individuals at different time periods, and whether the individual are in the same place over time. My dataset is ...
0
votes
1answer
68 views

mixed effects model output

lets say we have this: model2 <- lmer(milk.amount~(1|cow), data=milk, REML=FALSE) model1 <- lmer(milk.amount~(1|cow), data=milk) summary(model2) Linear mixed model ...
19
votes
2answers
310 views

How scared should we be about convergence warnings in lme4

If we a re fitting a glmer we may get a warning that tells us the model is finding a hard time to converge...e.g. ...
1
vote
0answers
52 views

including interactions in a mixed linear model in R (lme)

I'm trying to test for the effect of soil moisture on transpiration rates. I have plot-level data for 18 plots in 6 different stands of trees (3 plots x 6 stands). I want to treat "stand" as a random ...
0
votes
0answers
18 views

Assessing the effect of related variables using lmer in R

I am trying to run a model to describe the rate of water table drawdown in the soil. The predicted variable is rate, and I am interested in the effect of two categorical variables: (1) if the water ...
2
votes
1answer
40 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
46 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
26 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
24 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
62 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
1answer
76 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
68 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
30 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
50 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
104 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
51 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 ...
1
vote
0answers
37 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
91 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
15 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
39 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
80 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
33 views

Fitted values of 'lme' function result

I fitted a linear mixed model with R as follows. ...
2
votes
0answers
30 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
53 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
113 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
119 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
190 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
45 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
117 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
771 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
32 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
26 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
42 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
81 views

AICc results in R

I used the model: ...
0
votes
0answers
32 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: ...