lmer (& siblings glmer & nlmer) are functions in the R package lme4 that fit mixed effects models (ie, models that include fixed & random effects). These models can be non-linear in the sense that the dependent variable is transformed by a non-linear function (eg, logistic or log) to accommodate ...

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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 (...
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18 views

Interpretation and visualization of lmer output

I am trying to correctly interpret the output of my lmer-model and I also want to visualize an interaction contained in the model based on the intercept values. My variables and levels are Training ...
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35 views

difference in results of mixed effects model in nlme and lmer4 package

Can anyone please tell me why the results of random slope model is different for the same dataset when I use lme and lmer. I first fitted a random intercept model as follows using both lme as well ...
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30 views

collinearity in linear mixed effects model

I have one dependent variable (continuous data) and 4 independent data (mix of continuous and count) collected over 35 years across several states. I am using a linear mixed effect models with a ...
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1answer
59 views

Linear mixed effect models with two independent variables

I am estimating a random intercept and a random slope model using the following R code. My dependent and independent variable are both continuous. ...
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29 views

R-squared for linear mixed effects model [duplicate]

I ran linear mixed effects model in R. model<-lmer(yld ~ rain + (1+rain|state),data=data,REML=FALSE) Is there any way I can generate an R-squared for the ...
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13 views

difference between mixed effect and a simple ANCOVA

So I have collected data for 50 years of my dependent variable (continuous) data (x), independent (continuous) variable (y) across 10 locations. My null hypothesis is that the regression slopes ...
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1answer
42 views

Are best linear unbiased predictions (BLUPs) a good indicator of the mean value for that random effect member?

I have data on prices of houses in different districts, and would like to determine how expensive different districts are when it comes to buying a house. However, houses vary with respect to ...
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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 ...
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32 views

Mixed modelling with lmer

I've read multiple posts on model fitting using lmer(), but I saw multiple versions of using the error term which made it confusing for me. I have a factorial ...
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19 views

How to model a multiplicative effect of a parameter

I am having difficulty in fitting a model on data. Basically, I have data about the evaluation of phenotypic property (i.e. hard) of 65 palm trees by 5 judges. As an evaluation scheme, each judge ...
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27 views

Recovery of Standard Errors of Random Effects in Lmer

I'm analysing data with a nested structure with the lmer-function of the Lme4 package in R. I'm interested in the estimation of the confidence intervals of the random effects (is the score of class1 ...
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69 views

Variance component analysis with lme4

I am beginner with lme4 and I am seeking some advice on how to carry a variance component analysis. The data come from a real-world scenario, not from a designed experiment, resulting in a complex ...
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19 views

Do I need by-item effects in my lmer model, with gain scores as DV?

I'm attempting to fit a relatively straightforward linear model in R, but am in doubt as to whether by-item effects should be included in the model. Any input would be most appreciated! Study design: ...
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41 views

Comparing slopes in mixed-effect model

My data looks like the attached picture. The dependent variable indirectly measured physical activity. I tried to use mixed-effect model rather than RM Anova, because my actual data is imbalanced. ...
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46 views

In an experiment w/binomial responses, some subjects gave the same answer for all trials. [How] can a Mixed Effects model (R's lmer) deal with this?

I recently ran a pilot of an experiment on Amazon's Mechanical Turk. In the experiment, participants read 5 items, and answered a yes/no question about each one. A between-participants factor was ...
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23 views

How to account for multiple & varying amounts of observations per factor level & still retain info? As a random effect in GLMM or take the mean?

I would appreciate any help! Specifically I would like to know which option is best. Question Does Var2 influence Var1 in relation to the factor(Ind), and does Var3 & Var4 also have some effect. ...
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1answer
70 views

anova type III test GLMER wiht R

I am fitting a GLMER with lmer R package. I'm looking for an anova table with p-value shown therein, but I cannot find any package that fits it. Is it possible to do it in R? The model I am fitting ...
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1answer
58 views

Multilevel modeling: longitudinal data with within-subjects factors

I have a data set with experimental data that I am analysing with multilevel modeling. Data are structured as follows: 24 Sessions 6 Subjects per Session 10 Rounds per Subject There was one ...
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20 views

Should I control for random effects of participant in an individual differences design?

I'm trying to analyse a survey study in which I'm interested in the way that individual differences between my participants influence how they respond to my stimuli. The stimuli are pieces of writing ...
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62 views

Multiple comparisons with interactions of mixed lmer model and how to report them

Assume I test a number of patients repeatedly over time to see how a certain treatment changes their skin conductance in response to a certain colour (cond) after 2 months, 4 months, ... etc. I test ...
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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 ...
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1answer
1k views

Lmer model fails to converge

My data is described here What can cause a "Error() model is singular error" in aov when fitting a repeated measures ANOVA? I am trying to see the effect of an interaction using ...
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39 views

Differences between lsmeans and difflsmeans

I've created an lmer model. The effects of one of my treatments, "Fertilizer" varies depending on whether I use lsmeans or ...
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64 views

Linear Mixed Model for Longitudinal Data: Continuous vs. Discrete Time Parameter

I would like to conduct a power analysis for a linear mixed model with fixed effects for Treatment (two levels) and Time (four ...
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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 ...
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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 ...
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52 views

Should I be using a GLMM?

I'm looking at the influence of pollen type on whether a flower sets fruit (i.e., yes or no = 1 or 0). Then looking at number of seeds per fruit (1-6 possible). I was told I should use lmer, however ...
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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 ...
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108 views

lme / lmer - split-plot with Non orthogonal subdesign

I have an agricultural field experiment (testing a plant protection agent): Split plot design with: ...
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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 ...
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167 views

lmer() parametric bootstrap testing for fixed effects

I am performing a parametric bootstrap to test whether I need a specific fixed effect in my model or not. I have mainly done this for exercise and I am interested if my procedure so far is correct. ...
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41 views

Two-way interaction: interpret output from LMM in lmer

I have asked a question in this topic relating interpreting two- and three-way interactions in this link: How to interpret 2-way and 3-way interaction in lmer? ...
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34 views

Interpretation of three-way interaction in an output of lmer

I am using lme4 to run a three-way interaction model. I have three independent variables: animal (rat, lion, dog), color (red, green, blue) and sex (male, female). The baselines are as follows: ...
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2answers
97 views

A good source to understand interaction in LMM?

I would like to know more about interaction in LMM using lmer. Can you recommend me any books, articles, websites?
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25 views

Do I need a planned contrast or post-hoc analysis when doing LMM in R?

I am doing a LMM in R and would like to know if I need to do a planned contrast or a post-hoc analysis. From my understanding, the LMM in R already provideds me a planned contrasts and if I have ...
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1answer
107 views

Is it worth reporting small fixed-effect $R^2$ (marginal $R^2$), large model $R^2$ (conditional $R^2$)?

In a mixed model analysis (lme4 + lmerTest for R), I want to analyse the effect of 3 predictors, say A, B and ...
2
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1answer
39 views

When no model comparison, should I use REML vs ML?

I'm running LMM, and I will make no comparison of models. Could I ask which one should I use between REML and ML?
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1answer
31 views

Does the first line of interaction output from lmer contain all levels of variables?

I am using LMM from lmer to interpret my data. As the system of its output is dummy, so it should mean that the number of levels is always the same in every line of output. For example, if I have ...
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54 views

How to incorporate time varying group covariates in linear mixed effects model

I have a continuous response $Y_{ij}$ after taking repeated measures in an individual $i$. Altogether I measure $Y_{ij}$ 5 times (j=1..5) under different types of subject motion: still1, still2, nod, ...
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68 views

Multilevel model specification for count data (with overdispersion) in R

I would like to specify a multilevel model including the following variables: DV: count data, i.e. a score value between 0 and 13 (resulting from an additive index) for each individual Individual ...
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1answer
116 views

Is it necessary to exclude all nonsignificant parameters to choose the best model?

I'm running LMM models and could I ask if I can just report the model after comparing random intercept with random intercept and slope model without excluding nonsignificant factor?
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16 views

Does GLMM or LMM already give us planned contrasts?

I use GLMM and LMM to find significant factors for my data. And could I ask if the results from these two models already give me planned contrasts? Or do I need to run them separately?
2
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46 views

lmer giving worse performance than lm

I am having trouble training a model for nested data about house prices. Lets say my data looks like following: ...
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50 views

LMM models with two difference reference categories yield two different results

I have run LMM models with different reference categories and this yield different results: ...
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1answer
52 views

Fitting random intercept and slope in lmer for lme4.

If I would like to fit random intercept and slope and if I write it as (color|writer) compared to (1+color|writer), are they the same?
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1answer
85 views

Notation for multilevel modeling

The formula one needs to specify for training a multilevel model (using lmer from lme4 R ...
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249 views

Meaning of a convergence warning in glmer

I am using the glmer function from the lme4 package in R, and I'm using the bobyqa optimizer ...
2
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1answer
149 views

Binomial count data - use glmer, lmer or just average it all?

I'm new to both mixed-effects models and R, so please excuse me if this is a bit of a silly question! I'm struggling with choosing the best method to analyse my data for a speech perception study, and ...